Chinese researchers have developed a high-energy lithium-metal primary battery that combines long endurance with powerful bursts while operating at temperatures as low as -40°F (-40°C).

Developed by a team led by researchers from the Dalian Institute of Chemical Physics under the Chinese Academy of Sciences (CAS), the 25Ah pouch-type battery is designed to maintain stable performance in extreme cold.

According to Chinese online media reports, validation tests showed that the battery achieved an energy density exceeding 750Wh/kg at a low discharge rate.

The technology could support applications requiring reliable, high-energy power in harsh and low-temperature environments.

High-energy battery

The new lithium-metal primary battery is designed to combine high energy density, long storage life and rapid power delivery, while continuing to operate reliably in temperatures as low as -40°F.

The researchers developed a 25Ah pouch-type lithium-metal primary battery that achieved an energy density of more than 750Wh/kg under low-rate discharge conditions, according to Science and Technology Daily. Testing by the safety laboratory of the China Electronics Standardization Institute also found that the battery could increase its discharge rate by as much as 100 times, enabling short bursts of high-current output at up to 10C, reports the Global Times (GT).

The C-rate indicates how quickly a battery can charge or discharge relative to its rated capacity. A 1C discharge means a battery can theoretically deliver its full rated capacity in one hour, while a 10C discharge allows the same capacity to be delivered in roughly one-tenth of an hour. This capability is particularly important for primary batteries, which are designed for single-use operation and are not intended to be routinely recharged.

At room temperature, the new battery reportedly reaches a specific power of 4,487W/kg. It can sustain discharge at 4C and deliver short bursts at up to 10C, addressing a major limitation of conventional lithium primary batteries, which can offer high energy density and long shelf life but may struggle to release large amounts of energy rapidly.

Cold-ready battery

The battery also demonstrated significant performance at extreme cold. At -40°F, it retained an energy density of 447Wh/kg when discharged at 1C. Its annual self-discharge rate remained below 1 percent, indicating that the battery can retain most of its stored energy during extended periods of standby, reports GT.

The combination of high specific energy, low self-discharge and high power output could be valuable in situations where batteries must remain ready for long periods but suddenly deliver substantial power. Potential applications include drones and robots operating in remote locations, spacecraft systems, field-deployed sensors, rescue equipment and other devices where regular battery replacement or recharging is difficult.

Primary batteries are particularly useful in applications where charging infrastructure is unavailable or impractical. They can remain stored for long periods and provide power immediately when required, making them relevant to military operations, emergency response, rescue missions and forest-fire monitoring.

According to the team, they achieved the performance improvement through a new cathode material based on a high-entropy oxide. The team has also established a pilot production line with an annual capacity of 10 tons, providing a pathway from laboratory-scale material development toward battery manufacturing.

The battery has completed third-party testing and is undergoing additional validation for potential use in drones, robots, spaceflight simulators, and field sensor nodes. Further testing will determine how the technology performs under specific operating conditions and whether it can be scaled for broader commercial applications.

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US-based Agility Robotics is preparing to launch its Digit V5 humanoid robot, with the company positioning it as a step toward safer human-robot collaboration in warehouses and factories.

The robot is designed to operate alongside workers without traditional safety fencing, addressing a key challenge in deploying humanoids in real-world workplaces.

Digit V5 is expected to support 20-hour operational days and use interchangeable end-effectors for different material-handling tasks, with autonomous tool changes planned for the future.

Recently, Agility Robotics revealed its plans to go public through a $2.5 billion SPAC deal, raising over $620 million to fund product development, research, and expansion.

Robots go cageless

Agility Robotics is preparing to deploy its next-generation Digit V5 humanoid robot to early customers in December, marking a major step toward wider commercial use of humanoid machines in industrial environments.

Digit V5 is designed specifically for warehouse and factory operations, where it can work alongside people without requiring the extensive safety fencing typically used around industrial robots. The humanoid platform combines a human-scale form factor with autonomous mobility, allowing it to navigate facilities and perform material-handling tasks in spaces designed for human workers.

Agility says Digit V5 incorporates upgraded safety systems intended to let the robot operate in close proximity to people. This could eliminate the need for dedicated cages and barriers that can consume valuable floor space, require costly facility modifications, disrupt traffic patterns and force changes to existing workflows, reports Humanoids Daily.

The ability to operate without conventional fencing could make Digit V5 particularly useful in crowded warehouses and factories where installing a dedicated robotic enclosure is impractical. Workers could also move through areas where the robot is operating, potentially allowing more flexible collaboration between humans and machines.

Agility expects early customer deployments to validate Digit V5’s safety capabilities under real-world conditions before broader production begins. The company believes the technology could expand humanoid applications beyond logistics and manufacturing into sectors such as retail and pharmaceuticals, where earlier systems faced greater operational restrictions.

Advances robot safety

Agility is placing safety at the center of its next-generation Digit V5 humanoid robot, with a new system designed to let it operate in close proximity to people without traditional safety fencing.

The robot combines cameras, sensors and software that can detect and interpret people in its surroundings with hardware designed to respond safely to unexpected movements. Its proprietary cycloidal actuators in the hips and knees provide the strength and dynamic stability needed to react quickly without losing balance, dropping a payload or falling.

Agility has tested this capability by suddenly removing the surface beneath the robot, prompting it to take a corrective step and maintain its load. The company considers this dynamic stability an important part of its overall safety approach.

Digit V5 also introduces other features intended to support safer and more flexible operation. Its battery system is designed to support more than 20 hours of work per day, potentially allowing one robot to operate across three shifts. The humanoid also uses an ISO-standard flange that allows it to work with a broad range of robotic end-effectors. Agility has demonstrated Digit changing grippers and plans to eventually enable autonomous tool changes.

These capabilities could expand the robot beyond bulk material handling into tasks such as kitting and sorting, while maintaining the safety requirements needed for workplaces where humans and robots operate together.

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DEEP Robotics’ intelligent robots are helping researchers observe Tibetan antelopes in the high-altitude Serling Tso Nature Reserve in China.

Located at an average elevation of 4,700 meters (around 15,420 feet), the reserve becomes a key observation site between July and September, when large herds return with newborn calves during the annual migration season.

The robots captured footage of the animals migrating, nursing, and foraging around Cuo’e Lake, providing researchers with visual data that could support wildlife behavior.

Recently, Deep Robotics’ DR02 humanoid showcased enhanced mobility, running on grass, jumping obstacles, climbing stairs, and operating near hazardous electrical infrastructure for industrial applications.

Robots aid wildlife

At an average elevation of about 4,700 meters, China’s Serling Tso Nature Reserve provides an important habitat for Tibetan antelopes. From July through September, large herds return to the region with newborn calves, creating an ideal period for researchers to study migration, nursing and feeding behavior.

During this year’s migration season, DEEP Robotics deployed its robots around Cuo’e Lake to support wildlife research and ecological conservation. The machines captured natural footage of Tibetan antelopes while minimizing human interference, providing researchers with valuable visual data for long-term population and behavioral studies.

Advancing into High-Altitude Ecological Zones – Intelligent Robots Assist in Scientific Observation of Antelopes pic.twitter.com/QvNNUk1yeH

— DEEP Robotics (@DeepRobotics_CN) August 10, 2026

DEEP Robotics has previously used robotic systems for high-altitude wildlife observation. In 2025, its X30 quadruped robot operated in the Hoh Xil region at an elevation of around 4,800 meters (around 15,750 feet). Its biomimetic design helped it blend into the environment and reduce disturbance to animals.

This year, the company deployed its Lynx M20 wheeled-legged robot in the Serling Tso Reserve, primarily for close-range visual documentation. The robot was required to operate across soft meadows, uneven permafrost and scattered gravel, where conventional equipment can struggle with stability.

Cold temperatures, rain, snow and other harsh weather conditions further complicate fieldwork, highlighting the potential of rugged robotic platforms for scientific observation in extreme environments.

Lynx M20 advances

DEEP Robotics’ Lynx M20 wheeled-legged robot is being used to support ecological research in the challenging high-altitude environment in Serling Tso Nature Reserve.

Designed for all-terrain operation, the Lynx M20 combines the speed of wheeled movement with the obstacle-crossing ability of legged locomotion. Its IP66 protection rating helps shield the robot from dust and water, while its operating temperature range of -20°C (-4°F) to 55°C (131°F) allows it to function in unpredictable plateau conditions.

The robot is also equipped with LiDAR and depth cameras that enable it to perceive changes in terrain, including meadows, uneven permafrost and gravel slopes. Using this environmental data, the system can adjust its posture and movement in real time, helping it maintain stability while navigating difficult ground.

A key advantage is its low-interference operation. Tibetan antelopes are highly sensitive to unfamiliar sounds and movements, making conventional close-range observation difficult. The Lynx M20’s relatively quiet movement allows researchers to approach herds with less disturbance and remotely document behaviors such as migration, grazing, and nursing.

Researchers observed the robot approaching a herd near Cuo’e Lake without causing the animals to flee. According to DEEP, the exercise demonstrates how increasingly capable mobile robots can extend scientific monitoring into remote and extreme environments.

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A foldable, self-propelled pontoon barge has played a key role in rescuing more than 6,000 stranded students and staff from a flood-hit region in southern China.

The rapid-deployment vessel was used during evacuation efforts in the Guangxi Zhuang Autonomous Region after flooding due to Typhoon Maysak inundated communities, according to Chinese media reports. The modular barge can be assembled in just over 10 minutes, carry more than 500 people per trip, and transport loads exceeding 66.1 US tons. 

According to its manufacturer, the platform is engineered to operate reliably in harsh environments, including high-altitude regions up to 10,800 feet (3,300 meters) above sea level and areas with extreme cold.

Pontoon powers rescue

The self-propelled pontoon barge helped to evacuate more students and staff trapped after floodwaters nearly five meters deep cut off the campus.

The modular vessel, described by Chinese Foreign Ministry spokeswoman Mao Ning as “China’s real-life transformer,” played a central role in a large-scale evacuation at Guangxi Logistics Vocational and Technical College in Guigang, Guangxi Zhuang Autonomous Region, reported the South China Morning Post (SCMP). 

The rescue operation took place after torrential rains left the college campus submerged under nearly five meters (16.4 feet) of floodwater, cutting off thousands of people from surrounding areas. According to China’s state news agency Xinhua, conventional rescue methods initially struggled to cope with the scale of the emergency.

Emergency teams first relied on inflatable rescue boats and assault boats to reach those stranded. While effective for small-scale operations, these vessels could transport only a limited number of passengers at a time, making the evacuation process slow and difficult.

To accelerate the rescue effort, the state-owned China Anneng Construction Group, China’s emergency rescue force, deployed three heavy-duty self-propelled pontoon barges to the flooded area between Wednesday night and Thursday. The arrival of the modular barges dramatically increased evacuation capacity, allowing rescuers to move hundreds of people during each trip. By midday Thursday, every student and staff member had been safely evacuated, according to Guangxi Television.

Heavy-duty lifeline

The pontoon barge used in the operation measures approximately 60 meters in length and eight meters in width. It is capable of carrying more than 500 passengers in a single journey while supporting a total payload exceeding 66.1 US tons. Unlike conventional floating bridges or barges that require external towing, the vessel is equipped with its own propulsion system, enabling it to travel at speeds of up to 6.7 mph (10.8 km/h) even when fully loaded.

One of its biggest advantages is its rapid deployment capability. China Anneng said the modular system can be transported to a disaster site, assembled, and placed into operation in just over 10 minutes. Its foldable design allows emergency responders to quickly establish a large-capacity transport platform without relying on permanent infrastructure.

The rescue barge is regarded as one of China’s most advanced modular heavy-duty water rescue systems. It was specifically developed to address one of the biggest challenges during major floods—transporting large groups of people, emergency responders, vehicles, and heavy equipment across inundated areas or rivers made impassable by rising water, according to the SCMP.

The vessel is manufactured by China Harzone Industry Corporation, a subsidiary of the state-owned China State Shipbuilding Corporation (CSSC). The company says the platform is designed to operate reliably in demanding environments, including high-altitude regions up to 10,800 feet (3,300 meters) above sea level and areas experiencing extremely cold temperatures.

CSSC noted that the high-tech rescue platform has been widely deployed in domestic emergency response operations since 2020. Its successful use during the Guangxi floods demonstrates how rapidly deployable modular engineering systems are becoming an increasingly important tool for large-scale disaster response, enabling emergency teams to evacuate thousands of people far more quickly than traditional rescue boats alone. thousands of people far more quickly than traditional rescue boats alone.

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As the World Cup fever grows around stars like Messi and Ronaldo, Shanghai hosts a unique penalty shootout featuring humanoid robots.

At MWC Shanghai 2026, humanoid robots are stepping up to the spot in the Humanoid Robot Football Penalties Challenge, testing the limits of robotics,
AI, machine vision, and real-time motion control.

According to Chinese media outlets, the event showcases how embodied AI performs under pressure, highlighting next-generation autonomous technology through football-inspired challenges.

Ahead of the 2026 FIFA World Cup, Hyundai Motor recently launched a football-themed campaign featuring Boston Dynamics’ Atlas humanoid robot.

Humanoid football test

On its opening day at MWC Shanghai 2026 on June 24, the spotlight quickly shifted from keynote speeches to a live demonstration of embodied AI in action: the Humanoid Robot Football Penalties Challenge.

Held within the Mobile AI Innovation Frontiers Zone at the Shanghai New International Expo Centre, the event is designed as a controlled stress test for real-time autonomous decision-making, where humanoid robots must read the goal, judge angles, and execute penalty kicks without pre-programmed sequences, external control, or resets, reported CGTN.

While official details of the participating humanoid robots remain limited, videos circulating online suggest models from Booster Robotics and Unitree Robotics taking part in the challenge.

In the penalties challenge itself, participating humanoids are evaluated on perception accuracy, balance control, motion planning, and adaptive response under game-like pressure. Each robot must independently interpret ball position and goalkeeper movement before committing to a strike, making split-second corrections based on sensor feedback.

The format escalates through semi-finals and a final scheduled for June 25, intensifying constraints to simulate high-pressure competitive conditions. By turning a universally understood sports moment—the penalty kick—into a robotics benchmark, the showcase highlights how far embodied AI has progressed toward coordinated, human-like physical intelligence in unpredictable environments.

Atlas soccer showcase

In a recent football demonstration by Boston Dynamics, an Atlas robot is shown standing before a large display screen, closely tracking player movements, body positioning, and in-game reactions across football footage. After each clip ends, Atlas moves into a practice zone where it immediately attempts to reproduce the actions it has just observed, effectively linking visual perception with physical execution in real time.

The footage highlights a series of football-inspired motions. In one sequence, the robot shifts its weight, swings a leg forward, and smoothly guides a ball across the floor with controlled contact. It then progresses through rapid training drills focused on balance, coordination, and timing. As the session continues, Atlas’s movements appear increasingly fluid, suggesting the system is being evaluated not only for strength but also for agility, reflex response, and adaptive motor control.

Some of the most notable moments show Atlas imitating human emotional reactions. After completing a drill, it raises its arms in celebration, mirroring a footballer’s goal celebration. In another instance, it drops to one knee and pauses, recreating an injury response seen in match footage it had just observed.

Hyundai Motor Company, parent of Boston Dynamics, described the demonstration as Atlas’s first exposure to football under its “School of Football” initiative. The company has also indicated potential plans to showcase Atlas and the quadruped robot Spot at the FIFA World Cup, though their exact roles remain undisclosed.

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DEEP Robotics has demonstrated its new wheeled-legged robot in action, designed to handle challenging industrial operations across complex terrain.

M20S introduces significant improvements over M20 in payload capacity, mobility, durability, and endurance, positioning it as a new benchmark for industry-grade wheeled-legged robots.

Built for all-terrain performance, the Lynx M20S is designed to support a wide range of inspection, logistics, and field operations where reliability and adaptability are critical.

Recently, Deep Robotics unveiled new footage of its DR02 humanoid traversing rough terrain, climbing stairs, and carrying equipment, which is built for industrial and hazardous-environment operations.

Mastering rough terrain

LYNX M20 is a wheeled-legged robot designed for industrial operations in challenging terrain and hazardous environments. The company describes it as the world’s first wheeled-legged robot built specifically for demanding field applications, including power inspection, emergency response, logistics, and scientific exploration.

In this newly released demonstration video, DEEP showcases the capabilities of its Lynx M20S wheeled-legged robot in some of the world’s most demanding environments. The footage follows the robot traversing rugged mountain terrain, crossing icy rivers up to 31.5 inches (80 centimeters) deep, and operating in temperatures as low as -22°F (-30°C).

The Lynx M20S is also shown climbing steep 45-degree slopes and navigating rocky, uneven landscapes that would challenge conventional mobile robots. At elevations reaching nearly 17,000 feet (5,177 meters), the robot maintains stability and mobility while carrying out its mission in harsh outdoor conditions. The video highlights the platform’s combination of wheeled speed and legged agility, enabling it to tackle obstacles, extreme weather, and difficult terrain.

According to DEEP, the Lynx M20S, designed for industrial inspections, emergency response, and field operations, demonstrates how advanced robotic mobility can extend autonomous operations into environments that are often inaccessible or hazardous for human workers.

Next-gen field robot

M20S, weighing 77 pounds (35 kilograms), combines the speed of wheeled mobility with the adaptability of legged locomotion. It can navigate narrow spaces with as little as 50 cm of clearance, climb stairs up to 25 cm high, overcome obstacles up to 80 cm high, and handle slopes up to 45 degrees. The platform is designed to operate across rugged mountain trails, muddy wetlands, tunnels, pipelines, and disaster-stricken areas.

The M20 can carry a payload of 33 pounds (15 kilograms) and support a maximum load of 110 pounds (50 kilograms). It offers up to three hours of operation or 9 miles (15 kilometers) of travel on a single charge when unloaded, while carrying a 33-pound (15-kilogram) payload reduces endurance to 2.5 hours and 7.4 miles (12 kilometers). The robot can reach a laboratory-tested top speed of 5 m/s and an operating speed of 2 m/s.

For perception and navigation, the robot is equipped with dual 96-line LiDAR sensors providing a 360-degree by 90-degree field of view, along with wide-angle cameras and omnidirectional obstacle avoidance capabilities. Built for harsh environments, the platform carries an IP66 protection rating and can operate in temperatures ranging from -4°F (-20°C) to 131°F (55°C). Additional features include hot-swappable batteries, bidirectional lighting, OTA updates, and modular expansion options.

To improve operational endurance, DEEP increased the Lynx M20S’s single-charge runtime by 17 percent to 67 percent and added dual hot-swappable batteries. The upgrades help offset the high power demands of wheeled-legged locomotion and support longer, uninterrupted missions.

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Canadian robotics company Sanctuary AI has reported a significant achievement in industrial automation.

The firm said its system achieved a task success rate of more than 99.5 percent during a complex wire-plugging task for a global Tier 1 automotive supplier. 

The operation completed in 2.54 seconds, meeting the customer’s live-production benchmarks and demonstrating high-speed, reliable performance in a manufacturing setting. 

Sanctuary AI said the milestone highlights its strategy of deploying Physical AI on commercial robots to speed industrial adoption and support future industrial humanoids.

Factory automation leap

The achievement reflects Sanctuary AI’s strategy of deploying its Physical AI platform on existing and next-generation industrial robotic systems, rather than waiting for widespread commercialization of humanoid robots. This hardware-agnostic approach enables the company’s AI models to operate across different robotic platforms while accelerating adoption in manufacturing environments.

Sanctuary AI demonstrated high-performance Physical AI capabilities in an industrial manufacturing environment, achieving a task success rate exceeding 99.5 percent in a complex wire-plugging operation for a global Tier 1 automotive supplier. The system completed the task with a cycle time of 2.54 seconds, matching the throughput requirements of the customer’s live production line and meeting established industrial performance benchmarks.

The deployment focused on a plug-insertion process involving flexible wire assemblies moving along a conveyor. Such tasks are particularly challenging for automation because the cables can bend, twist, and shift position dynamically during transport, requiring continuous perception, adaptation, and precise manipulation.

According to the firm, the AI-powered robotic system successfully detected, tracked, aligned, and inserted the connectors while maintaining production-line speed and reliability.

“Manipulating a flexible wire into a moving target on a live conveyor is exactly the kind of contact-rich dexterity problem that has kept tasks like this out of reach for traditional automation. Solving it required models built around performance from day one with reliability, cycle time, and safety measured against real production benchmarks,” said Olivia Norton, co-founder and CTO of Sanctuary AI, in a statement.

AI power industries

Sanctuary AI develops Physical AI systems designed to enable robots to perform complex tasks in real-world industrial environments. Unlike traditional industrial automation, which relies on fixed programming for repetitive operations, Sanctuary AI’s approach combines advanced perception, reasoning, and manipulation capabilities, allowing robots to adapt to changing conditions and handle tasks that require dexterity and decision-making.

The company’s Physical AI platform processes information from cameras, sensors, and robotic actuators to understand its surroundings and execute actions in real time. This enables robots to identify objects, track movement, plan motions, and manipulate components with a high degree of precision. The technology is particularly suited to manufacturing environments where variations in object position, orientation, or movement make conventional automation difficult.

A key feature of Sanctuary AI’s strategy is its hardware-agnostic design. The AI can be deployed on existing industrial robotic systems as well as future robotic platforms, reducing the need for specialized hardware. This allows manufacturers to integrate advanced AI capabilities into current production lines while preserving existing infrastructure investments.

The platform is designed to automate labor-intensive tasks, including assembly, material handling, inspection, and component insertion. By combining real-time perception, motion planning, and adaptive control, Sanctuary AI aims to help factories improve productivity, maintain consistent quality, address labor shortages, and prepare for the next generation of intelligent industrial robots.

“By focusing on a performance-first approach to Physical AI models, we’re delivering value to customers today, on an AI platform that will also scale to the next generation of general-purpose systems,” said Norton, in a statement.

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A Seattle-based robotics company has developed a three-foot-tall humanoid robot designed for use in public attractions and venues.

The AI-powered robot named Codey can navigate autonomously, engage in conversations without remote human control, and make independent decisions.

While not yet capable of performing complex physical tasks such as fetching objects, Codey is being developed for future roles in healthcare, education, and hospitality.

The company says the robot is designed to interact naturally with people, particularly children, in public-facing environments.

Codey targets companionship

Codey is designed to serve as an interactive companion in public-facing environments. Standing about three feet tall, the robot features glowing hazel eyes, expressive facial animations, and a friendly appearance intended to engage users, particularly children.

Powered by AI, Codey can navigate autonomously, hold conversations, and make basic decisions without requiring a remote human operator. Unlike many robots that rely heavily on teleoperation, Codey is designed to function independently, enabling more natural and responsive interactions with people. The robot uses a combination of sensors, onboard computing, and AI software to understand its surroundings and communicate with users in real time.

Mind Children plans to conduct pilot studies this year in museums, hotels, and art galleries to gather data and refine Codey ahead of mass production. One of the company’s near-term objectives is to enable the robot to perform simple physical tasks, such as pressing buttons. A second-generation version of Codey is scheduled for release in 2027. To support development, Mind Children has launched a crowdfunding campaign and has raised more than $600,000 toward its $1 million funding target.

In the longer term, Codey is expected to be introduced into healthcare, education, and hospitality settings. Potential applications include assisting visitors with information, providing companionship, supporting learning activities, and helping organizations deliver more engaging customer experiences.

Embodied AGI advances

At the core of Mind Children’s robotics platform is Hyperon, the decentralized artificial general intelligence (AGI) framework developed by SingularityNET. The system is designed to give robots advanced cognitive capabilities that go beyond traditional rule-based automation, enabling them to reason, learn, adapt, and make decisions in dynamic real-world environments.

By integrating Hyperon into its humanoid robots, Mind Children aims to create machines capable of understanding context, processing complex information, and responding more naturally to human interactions. The framework incorporates knowledge representation, reasoning engines, and human-inspired motivation systems that help robots prioritize tasks, pursue goals, and adapt their behavior based on changing circumstances. This approach is intended to move robots closer to exhibiting flexible, human-like intelligence rather than performing only pre-programmed actions.

Unlike conventional AI systems that rely on centralized computing and data control, Hyperon operates within SingularityNET’s decentralized ecosystem. This architecture allows AI services, knowledge resources, and computational capabilities to be distributed across a network, promoting collaboration, scalability, and interoperability among different AI agents and robotic platforms.

The partnership between Mind Children and SingularityNET positions the company among the first developers pursuing embodied decentralized AGI—an emerging field that combines advanced artificial intelligence with physical robotic systems. The goal is to create autonomous robots capable of perceiving, reasoning, learning, and interacting with the physical world while continuously improving their capabilities through decentralized intelligence networks.

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US robotics firm Faraday Future (FF) has unveiled its first-half embodied AI (EAI) robotics lineup, introducing a full-form Robot World that spans six major product series.

The company also launched what it describes as the world’s first Three-in-One EAI Robotics Education Ecosystem Strategy, aimed at connecting robotics education, industry, and consumer applications.

During an event at its new headquarters in El Segundo, California, Faraday Future debuted the Futurist humanoid robot and the FX Navi quadruped robot, with the latter priced at $1,990 and available for immediate sale and delivery.

The California-based firm also announced the FF Robotics Partner Program, designed to expand global collaboration across its robotics ecosystem.

Robotics ecosystem unveiled

FF has unveiled a broad EAI robotics ecosystem, introducing four new robots, an open developer platform, and what it describes as the world’s first Three-in-One EAI Robotics Education Ecosystem Strategy aimed at accelerating consumer and educational adoption of physical AI technologies.

Leading the launch is the All-New Futurist humanoid robot, positioned as FF’s flagship professional-grade platform. Standing about 5 feet 8 inches tall and weighing approximately 121 pounds (54 kilograms), the robot is 14 percent lighter than its predecessor and features a redesigned structure for greater stability and more natural movement. Equipped with 31 degrees of freedom and a knee-joint torque of up to 320 Nm, the humanoid can run at speeds approaching 11 mph (17.7 km/h).

According to the firm’s statement, it is powered by a dual-battery system that offers up to 6 hours of runtime. It is built on a Vision-Language-Action (VLA) architecture combined with a World Model for advanced perception, reasoning, and autonomous decision-making. The robot is designed for commercial reception, guided services, industrial handling, warehouse operations, and hazardous-environment tasks. Additional specifications and pricing will be announced at Automate 2026 in Chicago on June 22.

FF also launched the FX Navi, a quadruped robot designed for home and classroom use. Marketed as the first foundational EAI learning quadruped robot in the United States, Navi combines robotics hardware with a dedicated STEM education ecosystem. The robot features 12 motorized joints, weighs 8 kilograms, and can navigate everyday indoor environments. A smartphone inserted into the head module serves as its computing platform, supporting both iOS and Android devices.

Users can customize the robot through downloadable and printable 3D head designs, while over-the-air updates will continuously add new capabilities such as autonomous following, multimodal perception, and natural interaction. Navi starts at $1,990, with optional development and curriculum packages available for students, educators, and developers.

One brain strategy

The company also previewed two upcoming humanoid robots. Master Mini, approximately one meter tall, is designed for education and robotic sports competitions, while Nova, standing about 50 centimeters tall, is intended as an entry-level educational and companion robot for children.

FF said its robotics strategy is built around a “one brain, multiple forms” approach designed to power a wide range of embodied AI robots from a shared intelligence platform. At the core of the strategy is FF’s evolving EAI Brain, based on a Vision-Language-Action (VLA) architecture and World Model, supported by an open-source developer ecosystem. The company says the platform is designed to operate across different environments, perform tasks autonomously, and adapt to new applications through its Skills and Agent system.

Rather than focusing on a single humanoid robot, FF is developing multiple robot form factors under its EAI Robot World concept, allowing a common AI brain to be deployed across different devices and use cases. The ecosystem is further supported by an EAI Data Factory that gathers real-world operational data and a global industry network aimed at improving manufacturing efficiency and reducing costs. Together, these elements form an expanding ecosystem designed to support large-scale deployment of embodied AI technologies.

FF additionally launched its open developer platform, featuring tools such as Brain Blocks visual programming, natural-language coding, robot personality customization, motion-generation software, and SDKs for professional developers. Through its new Agent Skill Store and Developer Ecosystem Program, FF aims to encourage contributions from students, educators, researchers, and software developers while expanding robotics adoption across homes, schools, and industry.

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Chinese firm Alibaba has launched its first embodied AI model family, which links large language models with real-world robotic actions.

The Qwen-Robot suite was developed by Alibaba’s Tongyi Lab and is undergoing pilot testing with selected Alibaba Cloud enterprise clients.

The suite comprises three models focused on navigation, manipulation, and world modeling for robots operating in physical environments.

Alibaba said the models enable machines to perceive, reason, and interact with the real world, joining a growing global push to advance embodied AI beyond traditional chatbot applications.

Robots meet reasoning

Alibaba says its Qwen family of AI models has become very good at understanding the physical world. These models can recognize objects, understand spatial relationships, follow complex visual instructions, and reason about real-world environments. For example, a model can understand a command such as, “Go to the kitchen, find the red cup, pick it up, and place it on the shelf.”

However, understanding a task is different from actually performing it. While a vision-language model (VLM) can describe the steps needed to complete a task, it cannot directly control a robot’s movements. The challenge is connecting human language and visual understanding with the motor actions required to interact with the physical world.

This problem is difficult because robot training data is very different from internet data. Information collected from navigation systems, robotic arms, vehicles, and cameras comes in different formats and is expensive to gather. Simply combining all this data often creates conflicts rather than improving performance.

To address this, Alibaba developed the Qwen-Robot Suite, which includes three specialized models. Qwen-RobotNav focuses on movement and navigation. It helps robots follow instructions, navigate to locations, track targets, and support autonomous driving.

According to its website, Qwen-RobotManip focuses on physical interaction. It enables robots to grasp, move, and manipulate objects using a large training dataset collected from different robotic systems. Qwen-RobotWorld acts as a world model, predicting how environments may change and helping robots understand the likely outcomes of their actions.

Together, these models aim to enable robots to understand instructions, interact with objects, navigate environments, and make decisions in the real world.

Physical AI accelerates

Alibaba showcased Qwen-RobotNav on a Unitree Go2 quadruped powered by NVIDIA Jetson Thor hardware and a single low-resolution camera. The robot successfully navigated an unfamiliar apartment, following spoken instructions across multiple rooms without preloaded maps, while maintaining an inference latency of 196 milliseconds.

The company claims that Qwen-RobotManip, its robotic manipulation model, was trained on more than 38,000 hours of open-source data covering object handling and interaction tasks. According to Alibaba, the model recently achieved the highest score in the generalist category of the RoboChallenge real-world robotics benchmark, earning a process score of 59.83 and a task success rate of 45 percent.

The company also unveiled Qwen-RobotClaw, a robotics agent framework that enables Qwen models to use the Qwen-Robot suite as physical-world tools. In one demonstration, an agent searched for a restroom, identified an out-of-order sign, and independently rerouted to another location. Alibaba further open-sourced Chat2Robot, a browser-based platform for testing embodied AI interactions.

As competition in embodied AI intensifies worldwide, Alibaba has expanded its ambitions beyond language and multimodal software with the launch of its Qwen-Robot models. The move reflects a broader industry shift toward creating AI systems capable of understanding and interacting with the physical world.

Alibaba’s move comes as competition in physical AI accelerates globally. In the US, Google DeepMind is advancing Gemini Robotics, while Nvidia is expanding its robotics ecosystem through Cosmos, Isaac, and GR00T. Start-ups, including Physical Intelligence, Skild AI, and Figure AI, are also developing general-purpose robotic intelligence, according to the South China Morning Post.

China is strengthening its position by pairing its manufacturing advantages with growing investments in AI software for autonomous decision-making. The sector now spans AI developers, robotics firms, and EV makers. Companies such as Alibaba, Tencent, Unitree, AgiBot, UBTech, Galbot, Spirit AI, GigaAI, Xpeng, and Xiaomi are actively pursuing embodied AI technologies.

Chinese automaker Seres has unveiled its first humanoid robot, Xiaosai, marking the company’s entry into the rapidly growing embodied AI sector. The robot is designed with visual recognition, autonomous greeting, and voice interaction capabilities.

The launch highlights the automaker’s expanding focus on robotics, with several additional embodied intelligence robots expected to debut later this year as Seres broadens its presence beyond electric vehicles.

Recently, Hyundai announced plans to deploy over 25,000 Atlas humanoid robots in the US, targeting 30,000 annual units by 2028 with locally manufactured robot components.

Industrial humanoid debut

Chinese automakers are rapidly expanding into humanoid robotics, leveraging expertise in manufacturing, artificial intelligence, supply chains, and automation to develop a new generation of embodied intelligence systems.

The latest entrant is Seres, which has unveiled its first humanoid robot, Xiaosai. The announcement was made by Seres Group director and vice president Kang Bo, who released a video showcasing the robot and confirmed that several additional embodied intelligence products are currently under development and scheduled to make their official debut later this year, reports CNEVPost.

Thought more details are not available, the humanoid is reported to be equipped with visual recognition capabilities, can autonomously greet people, and supports voice-based interaction. Its introduction highlights Seres’ broader efforts to integrate advanced robotics into manufacturing operations.

The company’s factory already employs a range of specialized robots across AI-powered quality inspection, logistics delivery, and production-line collaboration. Among them are Xiaosai 01, which performs quality inspections for chassis assembly, and Xiaosai 02, which checks the exterior configuration of completed vehicles.

According to Seres, the facility’s smart hub coordinates more than 1,600 intelligent devices, while over 3,000 industrial robots operate in synchronization throughout the plant. The factory also incorporates technologies, including the Internet of Things (IoT), big data, digital twins, 5G connectivity, and artificial intelligence, creating a highly automated digital ecosystem, reports CNEVPost.

Automakers go the robot way

Seres’ move into humanoid robotics builds on earlier investments in embodied intelligence. In October 2024, the company signed a cooperation agreement with Volcengine, a subsidiary of ByteDance, in Beijing. The partnership focuses on intelligent robot technologies, including decision-making systems, control technologies, and human-machine augmentation, with an emphasis on multimodal cloud-edge collaboration.

The launch reflects a wider trend among Chinese automakers, many of which view humanoid robots as a natural extension of capabilities developed through electric vehicle production and intelligent manufacturing. Xpeng is among the companies accelerating efforts in the sector. Earlier this month, chairman and CEO He Xiaopeng personally assumed the role of “CEO” of the company’s robotics division to speed up commercialization and development.

BYD has also confirmed that it is developing humanoid robots and is exploring the possibility of selling them through its extensive dealer network in the future. Meanwhile, Chery-backed Aimoga has moved beyond development and into commercialization. The company has begun selling humanoid robots directly to consumers, with a retail price of 285,800 yuan (approximately $42,260).

As Chinese automakers continue investing in embodied AI, humanoid robots are increasingly becoming the next frontier of competition, transforming car manufacturers into major players in the rapidly evolving robotics industry.

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An engineer has developed an open-source ceiling-mounted robotic claw designed to tackle one of the constant challenges of family life—cleaning up clutter.

Called Stringman, the system uses cables suspended from four corners of a room to move a robotic gripper across the ceiling, locating and collecting items such as toys, clothing, and other household mess.

Powered by LeRobot-based firmware, the robot can identify objects, pick them up, and transport them to designated drop-off points.

According to its maker, the project’s software, hardware designs, and build instructions are available on GitHub. At the same time, ready-to-use kits are also being offered for users who prefer not to build the system themselves.

Stringman tackles clutter

The DIY cleaning robot is designed to tackle one of the most common household challenges—clutter left behind by children and pets.

Stringman is a cable-driven robotic crane that moves across a room using high-strength lines suspended from anchors mounted in its four corners. Rather than relying on a humanoid design or a mobile robot, Stringman uses a lightweight gripper that travels through the room’s airspace, identifying and collecting objects from the floor before transporting them to designated drop-off locations.

The project was created by Nathaniel Nifong, who believes many household tasks can be automated without the complexity and cost associated with humanoid robots. According to the project’s website, reducing the number of actuators significantly lowers the overall cost of robotics hardware. Stringman relies on just four motors and a two-finger gripper with a wrist mechanism, allowing it to perform basic pick-and-place tasks while remaining relatively affordable.

The robot is built on the open-source LeRobot platform and uses imitation learning to improve its grasping capabilities. Users can train the system through teleoperation, teaching it how to pick up various household objects. The software, firmware, mechanical designs, and build instructions are publicly available under an Apache 2.0 license, allowing enthusiasts to build, modify, and contribute to the project.

To organize items, users simply designate destinations such as laundry baskets, toy bins, or trash cans using clip-on fiducial markers. Stringman’s vision system maps these locations and generates a list of objects it believes should be collected. Users can review and modify these selections through an interface or manually click objects they want the robot to remove.

Open-source robot

One of the system’s biggest advantages is its reach. Unlike robotic arms that are confined to a limited workspace, Stringman can access much of an entire room. Its cable-driven architecture enables it to move from floor-level pickups to elevated shelves without requiring rails, wheels, or articulated limbs. Because it is powered directly from a wall outlet, it also avoids the charging downtime that limits many mobile robots.

The design incorporates active swing-cancellation algorithms to stabilize the gripper as it moves. This is particularly important because the gripper hangs approximately 50 centimeters below the suspension point, allowing it to reach beneath furniture and alongside obstacles. The software continuously compensates for momentum, helping maintain accurate positioning during movement, according to its website.

Privacy has also been a focus of the project. Stringman supports a fully local operating mode in which video processing and telemetry remain within the home network. Users who prefer remote access can connect the robot to an online account and monitor or control it through a web-based interface.

Despite its promise, the system remains a work in progress. The machine-vision models still require refinement, and certain objects—particularly flat items such as books—can be difficult for the gripper to handle reliably. The suspended cables also descend into the room while the robot is operating, creating practical limitations for occupied spaces.

Even with these challenges, Stringman represents an intriguing alternative to humanoid domestic robots. By focusing on a single household task and simplifying the hardware, the project demonstrates how practical home automation may emerge from specialized, low-cost designs rather than human-shaped machines. Future developments could potentially allow the robot not only to collect clutter into bins but also to return items directly to their proper storage locations.

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ABB Robotics has partnered with California-based bionic company PSYONIC to develop more dexterous robotic systems by leveraging real-world data from human prosthetic use.

The collaboration combines PSYONIC’s Ability Hand, a touch-sensitive prosthetic hand, with ABB’s GoFa collaborative robot to study how human-generated touch and motion data can train robots to perform delicate and variable tasks.

The initiative aims to address one of industrial robotics’ biggest challenges—grasping and manipulation—while improving automation capabilities and potentially reducing engineering time for handling applications by up to 30 percent.

“Human dexterity and the instinctive understanding of how to handle different objects is one of the most difficult things to replicate in industrial-grade robotics, but it’s a fundamental need for truly autonomous and versatile robots,” said Marc Segura, President, ABB Robotics, in a statement.

Human data dexterity

ABB Robotics and PSYONIC aims to tackle one of the biggest challenges in industrial automation: robotic dexterity. The collaboration combines ABB’s GoFa collaborative robot with PSYONIC’s Ability Hand, an advanced prosthetic hand equipped with touch sensing and compliant design, to train robots using real-world manipulation data generated by human prosthetic users.

Unlike conventional robotic training methods that rely heavily on simulations, the project uses human-derived touch and motion data to teach robots how to grasp, manipulate and interact with objects more naturally. The approach is aimed at improving robots’ ability to perform delicate, variable tasks that have traditionally been difficult to automate, such as handling fragile components, adapting to changing object shapes and operating in dynamic environments.

The initiative supports ABB Robotics’ vision for Autonomous Versatile Robotics (AVR), where robots can sense, reason, move and manipulate objects with greater autonomy. It also contributes to the development of physical AI systems capable of learning from real-world interactions and applying that knowledge with industrial-grade reliability.

According to ABB, dexterity remains a major technical bottleneck in robotics, and improved handling capabilities could reduce engineering time for automation projects by up to 30 percent. The companies are exploring applications across sectors including automotive, aerospace, packaging, logistics and life sciences.

PSYONIC is working closely with ABB’s research and development team to integrate touch-enabled manipulation technologies into robotic platforms. The partnership aims to narrow the gap between human and robotic dexterity, enabling more adaptable, productive and safer automation systems for industrial environments.

Touch powered robotics

The ABB GoFa is a collaborative robot designed to work safely alongside humans in manufacturing, assembly, material handling, packaging, and laboratory environments.

It can handle payloads of up to 26 pounds (12 kilograms) and reach up to 1.62 meters, offering a combination of speed, precision, and flexibility. Built-in force and power limitation technology enables safe human-robot collaboration with minimal safety barriers, while intuitive programming tools simplify deployment. With repeatability of up to 0.02 mm, GoFa is well suited for precision tasks and improving productivity.

On the other hand, the Psyonic Ability Hand is an advanced bionic prosthetic that provides multi-touch sensory feedback, helping users experience a more natural sense of touch. Its 200-millisecond closing speed allows fast, secure grasping, while 32 grip patterns—19 pre-programmed—support activities ranging from handling small objects to typing. The hand automatically adjusts thumb positioning for a stable grip and can be configured remotely via Bluetooth-enabled iPhone and Android apps.

Powered by a 2200mAh battery, it charges through USB-C in about an hour and delivers 6–8 hours of use. Its durable, IP64-rated design resists impacts, dust, and splashes. Beyond prosthetics, organizations such as NASA, Meta, and Apptronik use it for robotics research.

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New reports suggest that Boston Dynamics’ Atlas is approaching the autonomy needed for industrial deployment.

The assessment follows recent demonstrations by Boston Dynamics that indicate significant progress in developing general intelligence.

Experts suggest advancements now enable humanoid robots to adapt to unfamiliar environments and perform a broader range of tasks beyond preprogrammed actions.

Recently, the US robotics firm launched a campaign featuring Atlas, using football to showcase human-centered robotics, AI, and human-robot interaction.

Atlas gains intelligence

Boston Dynamics is making rapid progress toward commercializing humanoid robots, with its Atlas platform approaching the level of autonomy required for industrial deployment, according to a new report from KB Securities.

Analyst Kang Sung-jin said recent demonstrations by Boston Dynamics, Hyundai Motor Group’s US-based robotics subsidiary, point to major advances in the development of humanoid robot “general intelligence” — the ability to adapt to unfamiliar environments and perform a broad range of tasks without relying solely on preprogrammed instructions, reports The Korean Herald (TKH).

A key factor behind this progress is the company’s accelerated training framework. According to the report, Boston Dynamics can run simulations equivalent to millions of hours of robot training in a single day. The resulting behaviors and skills can then be transferred to a physical Atlas robot in roughly one hour, significantly shortening development cycles and enabling faster deployment of new capabilities.

The report credits strategic collaborations with Google DeepMind and Nvidia for helping drive these advancements. DeepMind contributes expertise in artificial intelligence and learning systems, while Nvidia provides the high-performance computing infrastructure needed for large-scale simulation and robot training.

Recent Atlas demonstrations also highlight notable improvements in physical intelligence and whole-body control. In one example, the humanoid robot moved a refrigerator using coordinated movements across its entire body, while another video showed Atlas performing dynamic kicking motions that required balance, agility, and precise motor control, reports TKH.

Kang said the demonstrations reinforce Hyundai Motor Group’s commitment to industrial humanoid robotics and position Boston Dynamics as a leading contender in the emerging market. He projects the company could secure 15 percent of the global humanoid robot market by 2035 and as much as 60 percent of the premium industrial humanoid segment.

Atlas industrial leap

Boston Dynamics says one of the key advantages of its new Atlas humanoid robot is a significantly reduced “sim-to-real gap” — a common robotics challenge where skills learned in simulation fail to transfer reliably to the physical world. The company attributes this improvement to Atlas’ simplified hardware design, which makes it easier to create highly accurate simulations for training.

Unlike many humanoid robots that use numerous actuator types and complex mechanical systems, Atlas relies on just two actuator types across its body. Its arms and legs are also designed symmetrically, simplifying both control and simulation. This streamlined architecture allows engineers to train the robot more efficiently in virtual environments and rapidly transfer those capabilities to the real machine.

Boston Dynamics also redesigned Atlas to eliminate cables running across joints, enabling continuous joint rotation while reducing wear and maintenance requirements. The added flexibility allows the robot to perform movements that are difficult for conventional humanoids.

The company highlighted Atlas’s ability to handle heavy industrial tasks. Although the robot was trained using loads weighing between 50 and 70 pounds (23–32 kilograms), it successfully moved a refrigerator weighing more than 100 pounds (45 kilograms) during testing. According to Boston Dynamics, such tasks require more than visual perception, demanding full-body coordination, weight anticipation, balance, and precise force control.

The company added that Atlas’s athletic feats, including handstands and backflips, serve a practical purpose by helping develop balance, agility, slip recovery, and endurance needed for real-world industrial environments.

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A Tawniese firm has unveiled its first humanoid robot capable of interacting with the physical world.

TM Technology, known primarily for integrated circuit design, has expanded its operations into sectors such as construction, green energy, and smart manufacturing, with support from its parent, Yinglin Group.

TM Technology said the humanoid robot combines advanced hardware and software as part of a broader intelligent platform strategy, representing a significant step in its efforts to develop next-generation AI-powered robotic systems.

Recently, Techman Robot from Taiwan unveiled its TM Xplore I humanoid at Nvidia GTC 2026 in San Jose, highlighting a collaboration with QCT and Nvidia.

Embodied AI emerges

As per reports, TM Technology’s newly unveiled humanoid robot combines AI, advanced manufacturing, biomimetic engineering, and multi-modal sensing technologies to operate in complex real-world environments. Designed as an embodied AI system, the robot features a layered architecture that mirrors key functions of the human nervous system.

At its core is an AI-powered “brain” responsible for semantic understanding, reasoning, task planning, and decision-making. A dedicated “cerebellum” subsystem manages balance, posture control, locomotion, and coordinated movement, enabling the robot to perform tasks with greater stability and precision. The platform also incorporates a sophisticated perception suite that combines 3D vision systems, LiDAR sensors, and force-sensing technology to create a detailed understanding of its surroundings and support real-time interaction, reports Taiwan News (TN).

The humanoid is equipped with multi-degree-of-freedom joints and dexterous robotic hands, enabling it to manipulate objects and perform a wide range of physical tasks. According to the company, the robot can handle transportation, inspection, assembly, and other precision operations that require coordinated motion and environmental awareness. Unlike traditional industrial robots that follow pre-programmed routines, the system is designed to adapt to changing conditions through learning-based interaction and intelligent decision-making.

TM Technology said the development marks a shift from conventional hardware manufacturing toward integrated intelligent platforms. The company expects initial deployment in factories and logistics environments, where autonomous robots can assist with repetitive and labor-intensive tasks, before expanding into healthcare, caregiving, and household service applications as the technology matures, reports TN.

Taiwan’s humanoid push

Another Taiwanese firm, Techman Robot, recently unveiled its next-generation humanoid robot, TM Xplore I. The robot reflects Techman’s strategy of combining artificial intelligence with industrial automation under its “See · Think · Act – Powered by AI Robotics” framework.

Unlike traditional bipedal humanoids, TM Xplore I features a humanoid upper body mounted on a wheeled mobile base, a design intended to improve stability, mobility, and operational reliability in factory environments. The platform combines autonomous navigation with dexterous manipulation, enabling it to transport materials, interact with workers, and perform precision tasks in industries such as semiconductor manufacturing, electronics assembly, and automotive production.

The robot is powered by Nvidia’s Jetson Thor computing module, providing high-performance edge AI capabilities for real-time decision-making. It also incorporates Vision-Language-Action (VLA) technology, allowing it to process visual and language inputs simultaneously and translate them into physical actions. Techman’s software stack supports multimodal sensor fusion, generative AI inference, and autonomous operation.

TM Xplore I further leverages Nvidia’s robotics ecosystem, including Isaac Sim for simulation-based training and testing, FoundationStereo for AI-powered depth perception, and Isaac GR00T for enhanced dexterity and autonomy. Together, these technologies enable faster deployment, improved adaptability, and more efficient automation in smart manufacturing environments.

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New research has found that humanoid robots could become effective playmates for humans, but only if their behavior aligns with people’s expectations.

A study by researchers at the Norwegian University of Science and Technology (NTNU) explored how people interact with humanoid robots during physical games.

The team conducted controlled laboratory experiments using Pepper, a social robot built to engage with humans, to better understand the experience of playing alongside or against a robot.

The findings suggest that robots can be enjoyable gaming companions when they act naturally and respond appropriately to the flow of play. However, mismatched behavior, awkward movements, or an overly competitive attitude can quickly frustrate users and reduce engagement during interactions.

Robot teammate test

Humanoid robots such as Pepper are designed to look and behave in ways that resemble humans, featuring recognizable traits such as heads, eyes, hands, facial expressions, and conversational abilities.

According to researchers, these human-like characteristics help people relate more easily to robots, but they also create expectations that robots will act in socially appropriate and predictable ways.

To better understand how people interact with robots during play, researchers conducted an experiment in which participants played a physical version of trash-can basketball with Pepper. The game involved throwing crumpled paper balls into a trash can from designated positions chosen to provide a balanced level of challenge for both the human participants and the robot.

The study examined two different gameplay modes. In one mode, participants cooperated with Pepper as teammates working toward a common goal. In the other, they competed directly against the robot. Researchers also varied the order of play, with either the human participant or Pepper taking the first turn.

By comparing these scenarios, the team evaluated how gameplay mode and turn order influenced player engagement, motivation, enjoyment of physical activity, and emotional responses.

The findings revealed that seemingly minor factors, such as who takes the first turn and whether the interaction is cooperative or competitive, can significantly affect how people perceive the experience. “Our observations show that robots can actually be good playmates, but only if they behave in ways that make sense to people,” said Yavuz Inal, associate professor at NTNU’s Department of Design in Gjøvik, in a statement.

Cooperative play wins

Participants generally reported the most positive experiences when the game began in cooperative mode. However, competitive play also proved highly engaging for many players. Several participants found competing against Pepper more exciting and motivating, particularly when they were allowed to start the game first, which increased their sense of control over the interaction.

Many players also experienced a strong sense of accomplishment when they outperformed the robot. Some even admitted that watching Pepper miss a shot added to the enjoyment. For these participants, competition with the humanoid robot created a fun challenge, clear objectives, and a rewarding sense of mastery that enhanced the overall gaming experience.

The study also found that participants became frustrated with Pepper for reasons similar to those that make people irritated with overly competitive friends or family members during board games.

Frustration was particularly noticeable when the robot started the game in competitive mode. Pepper’s slow pace, long pauses before taking a turn, and apparent determination to win often clashed with participants’ expectations of how a human-like playmate should behave. As a result, some players felt the robot lacked the responsiveness and natural flow needed for enjoyable gameplay. One participant likened the experience to playing against an “overworked printer with arms.”

According to the researchers, people expect robots cast as playmates to act like genuine players. “The results offer a glimpse into a future where robots not only assist us at work and in the healthcare system, but also participate in everyday activities such as play, exercise, and games,” said the team in a statement.

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While China dominates humanoid robotics headlines, a Korean firm showcased a humanoid learning complex motions through an open-source AI framework.

In a recent demonstration, ROBOTIS’ AI Sapiens learned the famous CORTIS REDRED Challenge motion using only smartphone video, eliminating the need for professional motion-capture systems.

The process combined video-based motion capture, motion retargeting, simulation-based reinforcement learning, and Sim2Real transfer.

According to the firm, the demonstration highlights how open-source tools can simplify humanoid robot training, enabling users to generate, learn, and execute full-body motions more easily.

Humanoid learns motion

ROBOTIS has demonstrated the capabilities of its AI Sapiens humanoid robot, an open-source platform for physical AI powered by DYNAMIXEL-Q actuators. The project is designed to make humanoid robot motion learning more accessible by using widely available hardware and open-source software tools.

In the demonstration, AI Sapiens learns and performs a complex full-body motion known as the CORTIS REDRED Challenge. Instead of relying on expensive professional motion-capture systems, the robot learns the movement from video recorded using a standard smartphone camera. This significantly reduces the cost and complexity of collecting training data for humanoid robots.

The motion-learning process begins with video-based motion capture. Human movements recorded on a smartphone are converted into digital motion data that can be processed by software. The captured motions are then passed through a motion retargeting stage, where the human movements are adapted to match the physical structure and joint limitations of the humanoid robot.

After retargeting, the robot is trained in a simulation environment using reinforcement learning. During this stage, the AI repeatedly practices the motion in a virtual world, allowing it to improve balance, coordination, and movement accuracy without risking damage to physical hardware. Simulation training also enables rapid testing and optimization before deploying the motion to the real robot.

Once training is complete, the learned behavior is transferred from simulation to the physical AI Sapiens robot through a Sim2Real pipeline. This process helps ensure that motions developed in the virtual environment can be executed successfully in the real world, despite differences between the simulation and the physical hardware.

Accessible AI robotics

ROBOTIS plans to release the motion generation and learning pipeline as open-source software, giving researchers, developers, educators, and hobbyists access to the tools used in the demonstration. The goal is to lower barriers to humanoid robotics development and enable a wider community to experiment with motion learning and physical AI systems.

According to ROBOTIS, AI Sapiens is a fully open-source humanoid robot platform designed for physical AI research and development. Standing 1.3 meters tall and weighing 34 kilograms, the robot features 23 degrees of freedom across its body, enabling a wide range of human-like movements.

The platform is powered by 23 next-generation DYNAMIXEL-Q quasi-direct-drive (QDD) actuators, including 14 QM-060 units and 9 QM-080 units. These actuators combine low gear reduction ratios, high-torque motors, and integrated control electronics to deliver high backdrivability, low impedance, and precise torque control, making them suitable for dynamic and compliant humanoid motion.

AI Sapiens is powered by an NVIDIA Jetson Orin NX 16GB computer, delivering up to 100 TOPS of AI performance for advanced robotics tasks. It supports Wi-Fi 5, Bluetooth 5.0, dual Ethernet ports, USB connectivity, and 24V/12V power outputs for connecting additional hardware.

The robot is powered by a 46.8V, 9000mAh battery. It is supported by a fully open-source ecosystem that includes hardware bills of materials, CAD files, source code, simulation assets, and development tutorials, enabling researchers and developers to customize and expand the platform.

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China has deployed robotic snakes to inspect power lines and help ensure a stable electricity supply.

The snake-like robots wrap around power lines and use onboard cameras and sensors to detect hazards such as damaged wires, worn components, and abnormal temperatures.

According to online media reports, the robots have inspected more than 80 miles (130 kilometers) of distribution lines serving exam sites near airport no-fly zones.

The system is three times more efficient than manual inspections, reducing the need for labor-intensive, hazardous work while improving reliability and safety.

Robotic grid guardians

Power utilities in southwestern China are using robotic snakes to inspect power lines, showcasing a new approach to infrastructure monitoring in environments where drones face limitations.

The snake-like robots have been deployed in Kunming, the capital of Yunnan province, where they move directly along power lines while inspecting critical electrical infrastructure. Equipped with cameras and sensors, the robots can identify faults such as broken wires, worn components, and abnormal temperature changes that could signal potential failures, reports the South China Morning Post (SCMP).

Developed by the Guandu District Power Supply Bureau, the robotic system has already inspected more than 80 miles (130 kilometers) of power distribution lines. According to its developers, the technology delivers inspection efficiency three times higher than traditional manual methods.

Unlike aerial drones, which are widely used for power-line inspections, the robotic snakes operate directly on the cables they monitor. This allows them to work in locations where drone flights are restricted, including areas near airport no-fly zones. The robots are also less vulnerable to high-voltage electromagnetic interference, a common challenge that can disrupt drone control systems and reduce image quality.

Meet the snake-like #robot patrolling power lines in #Kunming.

Slithering along cables, it uses onboard cameras and sensors to spot damage and overheating in real time. Even better, it draws power straight from the line, enabling autonomous 24/7 monitoring without interruption. pic.twitter.com/zXJq61oft4

— China SCIO (@chinascio) June 10, 2026

The system addresses several limitations of drone-based inspections, including restricted flight zones, weather dependence, and limited battery endurance. By providing continuous close-range monitoring of power infrastructure, the robotic snakes enable utility crews to quickly identify and address potential hazards, reports SCMP.

Intelligent grid inspectors

Chinese power utilities are deploying a range of robotic systems, including snake robots, robot dogs, drones, and surveillance cameras, to monitor electricity infrastructure and maintain reliable power supplies during the national college entrance exams.

The snake robot features a flexible, multi-jointed body that allows it to move along power lines and navigate around obstacles such as insulators. This design enables it to reach areas that are difficult for human inspectors and aerial drones to access. A camera and onboard sensors mounted in the robot’s head detect potential faults and safety risks, while a non-contact power-harvesting system allows the robot to draw energy directly from the power lines it is inspecting.

Following successful trials on multiple transmission routes, utility operators have expanded the robot’s deployment to more complex sections of the power grid. Robot dogs are also being used for inspections in high-voltage environments and other locations that are challenging or hazardous for human workers. Combined with drones and fixed monitoring systems, the robotic platforms provide continuous oversight of critical electrical infrastructure.

The deployment comes as approximately 12.9 million students sat for China’s National Higher Education Entrance Examination, known as the gaokao, one of the country’s most important academic tests. Reliable electricity is considered critical during the examination period, prompting utilities to adopt advanced robotic technologies to improve inspection efficiency and reduce operational risks, reports SCMP.

Humanoid robots may soon gain more human-like dexterity thanks to a new wearable device developed by researchers at the Massachusetts Institute of Technology.

The ultrasound wristband uses high-frequency sound waves to capture the movement of muscles, tendons, and ligaments beneath the skin, creating detailed data on human hand motions.

According to the team, the data collected by the system could be used to train robots to perform household tasks by replicating the dexterous hand movements used by humans.

Last year, researchers at the University of California San Diego developed a wearable AI system that accurately interprets arm gestures and controls robots, even during running, vehicle motion, or rough ocean conditions.

Wristband teaches robots

For robots to perform delicate tasks with human-like precision, they must first understand the complex movements of the human hand. Researchers have now developed a wearable ultrasound wristband that could help bridge that gap by capturing detailed muscle and tendon activity beneath the skin and translating it into robotic motion.

Tracking hand and finger movements is a key challenge in fields such as robotics and spatial computing. Existing solutions have significant limitations. Camera-based systems can struggle with restricted viewing angles and visual obstructions, while wearable devices based on strain sensors, inertial sensors, or electromyography often limit movement or lack the resolution needed to accurately capture continuous finger motions, according to the team’s study paper.

The new wristband builds on a series of advances in wearable ultrasound technology over the past several years. Researchers have steadily expanded the capabilities of ultrasound wearables beyond gesture tracking and robotics. In 2022, scientists demonstrated a wearable ultrasound device capable of continuously monitoring multiple internal organs. Subsequent developments included wearable systems for continuous heart imaging and bladder volume monitoring.

In 2024, researchers introduced a conformal ultrasound patch capable of tracking cerebral blood flow in three dimensions and an integrated wearable ultrasound system that monitored deep tissue activity with sub-millimeter resolution using a single transducer. More recently, flexible, disposable ultrasound patches were developed to reduce manufacturing costs.

Now, in a new study, researchers led by Xuanhe Zhao at MIT introduced a wearable ultrasound imaging wristband capable of tracking arbitrary hand configurations. The device uses high-frequency sound waves to image muscles, tendons, and ligaments inside the wrist, providing a detailed view of the mechanisms that drive hand movement.

Decoding human hands

The wristband could help robots achieve human-like hand dexterity by capturing the movements of muscles and tendons beneath the skin. The device incorporates a 256-channel wireless ultrasound imaging system that uses high-frequency sound waves to monitor structures inside the wrist responsible for controlling finger and palm motions.

The ultrasound data is processed by a hybrid Transformer–ResNet AI model capable of interpreting subtle muscle activity. The system continuously tracks all 22 degrees of freedom of the human hand, covering the full range of joint movements that allow fingers and the palm to bend, rotate, and coordinate complex actions. Achieving this level of tracking has been a longstanding challenge for hand-motion sensing technologies, reported AP News.

In laboratory tests involving eight volunteers, the wristband reproduced hand gestures with high accuracy and low latency, mirroring movements within 120 milliseconds. Researchers demonstrated the system’s ability to recognize all 26 letters of American Sign Language, highlighting its precision in capturing intricate finger configurations.

Because the wristband operates wirelessly, users can control robotic systems remotely without being physically connected or located in the same room. To showcase its capabilities, the team used the technology to manipulate three-dimensional objects in virtual reality and direct a robotic hand to play the piano.

Beyond teleoperation, researchers believe the system could be used to generate large-scale datasets of human hand movements, providing valuable training data for future humanoid robots and helping them learn complex manipulation skills more autonomously.

A new humanoid robot from China became one of the standout attractions at a major industrial exhibition after performing a Tai Chi routine.

Zoomlion’s Z01 bipedal robot demonstrated smooth, coordinated movements, highlighting its advanced motion control, dynamic balance, and human-like mobility.

The Tai Chi demonstration at KOMATEK 2026 in Istanbul showcased the robot’s ability to execute complex sequences with precision while maintaining stability throughout the performance.

In January 2026, the construction giant unveiled a full-chain AI system to drive intelligent transformation across machinery, manufacturing, management, and robotics.

Advanced balance display

While detailed specifications have not been released, Z01 is reported to feature millisecond-level motion response, long battery life, powerful onboard AI computing, and a high-degree-of-freedom design that enables smooth, natural movement. It also includes a built-in operating system that reportedly reduces robot development complexity by three to five times.

The robot’s Tai Chi routine showcased sophisticated motion control systems, coordinated full-body movement, and dynamic balance capabilities. By maintaining smooth transitions between poses and adapting its posture throughout the sequence, Z01 demonstrated the level of control required for real-world human-centered environments. Visitors closely followed the performance as the robot carried out the traditional martial art movements with remarkable consistency and coordination, according to a statement by Zoomlion.

Beyond the demonstration, Z01 represents a broader push into embodied AI and intelligent robotics. The humanoid robot is intended to support future applications that require close collaboration with people, including industrial assistance, guided services, and educational interaction. Its development reflects growing efforts to combine advanced software intelligence with robotic hardware capable of operating in dynamic environments.

“The debut of Z01 highlights Zoomlion’s growing commitment to embodied AI, with embodied AI robots and related emerging industries forming the company’s third growth curve,” said the firm in a statement.

AI robotics ecosystem

Zoomlion is advancing embodied AI through a technology stack that combines robotics hardware, intelligent software, motion control, and industrial automation. Building on years of investment in industrial IoT, the company has developed a strong digital infrastructure through Zvalley, its AI-powered industrial internet platform, supported by nearly 1,300 technical and R&D specialists.

Since 2024, the company has accelerated development of embodied intelligence systems by integrating robot hardware, core components, perception technologies, AI decision-making engines, motion-control algorithms, and software ecosystems into a unified framework. This approach enables robots to perceive their surroundings, make autonomous decisions, and execute complex physical tasks in dynamic environments.

By the end of 2025, Zoomlion had developed eight embodied AI robot prototypes spanning four categories, including humanoid and wheeled robotic platforms. These systems have been tested across real industrial settings, where they perform tasks such as logistics handling, factory inspections, loading and unloading operations, pre-assembly processes, and quality control. Operating in live production environments has allowed the company to gather valuable real-world data for training AI models and refining robot performance.

At Hannover Messe 2026, Zoomlion further demonstrated its technological progress through Robot Ops, an embodied AI development platform designed to coordinate intelligent robotic systems. The platform showcased autonomous decision-making, advanced motion control, multi-robot collaboration, and industrial deployment capabilities, highlighting the company’s efforts to transform embodied AI from research concepts into scalable industrial solutions.

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