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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An open-source quadruped robot named Q8botOne aims to provide an affordable, fully assembled robotic platform for hobbyists, researchers, and developers. Building on the original Q8bot’s low-cost, agile design, Q8botOne comes fully assembled and ready to use right out of the box.

The robot now packs programmable actuators into a palm-sized platform, delivering dynamic mobility in a robot compact enough to roam across a desktop.

According to its maker, the robot will soon be available through a Crowd Supply campaign, making quadruped robotics more accessible to a wider audience.

Agile quadruped arrives

Q8botOne is an upcoming open-source quadruped robot developed by Eric Wu to make advanced legged robotics more accessible to hobbyists, students, researchers, and developers.

Despite its small size, Q8botOne is capable of performing a range of dynamic movements typically associated with much larger and more expensive quadruped robots. The robot can walk, trot, and jump, demonstrating agile locomotion that makes it suitable for robotics research, educational projects, and experimentation with autonomous behaviors. By eliminating the need for users to source parts and assemble the robot themselves, Q8botOne significantly lowers the barrier to entry for anyone interested in legged robotics, Hackster reported.

One of the robot’s most distinctive features is its highly integrated design. Unlike many small quadrupeds that rely on numerous wires routed throughout the body, Q8botOne incorporates its electronics directly onto a custom central printed circuit board. This streamlined architecture reduces cable clutter, improves reliability by minimizing potential failure points, lowers overall weight, and simplifies maintenance and troubleshooting. The result is a cleaner and more refined appearance that sets the platform apart from many traditional DIY robotics projects.

The robot’s locomotion system is powered by eight DYNAMIXEL XL-series smart actuators. These actuators drive lightweight parallel-linkage legs constructed from Multi Jet Fusion (MJF) 3D-printed components and precision ball-bearing joints. This combination provides a balance of strength, durability, and low weight, enabling smooth, accurate movement. The mechanical design has been optimized to support dynamic maneuvers while maintaining structural efficiency, according to Crowdsupply. 

At the heart of the system is an ESP32-C3-MINI-N4 microcontroller that manages onboard processing and robot control. Power is supplied by a rechargeable lithium-ion battery equipped with integrated protection circuitry to enhance operational safety and battery management. The robot is designed to provide a convenient user experience, allowing owners to begin experimenting immediately after powering it on.

Open quadruped platform

Each Q8botOne package will include a custom wireless controller dongle that comes pre-paired with the robot.

The controller features a joystick, multiple buttons, and USB-C connectivity for both power and communication. When connected to a computer, the controller provides access to software tools that enable users to configure, monitor, and control the robot in greater detail. This setup allows beginners to quickly get started while also offering advanced functionality for experienced developers, reports Crowdsupply.

Expansion capabilities are another key aspect of the platform. A Qwiic-compatible connector enables easy integration of additional sensors from manufacturers such as SparkFun and Adafruit without requiring complex wiring. The robot also includes a UART interface that supports co-processors, such as a Raspberry Pi. This interface can supply up to 5V at 3A, allowing users to add more powerful computing hardware for applications involving computer vision, AI, autonomous navigation, or custom robotics research.

Continuing the philosophy of the original Q8bot project, Q8botOne will remain fully open source. Mechanical designs are being created in Onshape, and firmware, hardware schematics, and related design files are expected to be released through the ZeroWireRobotics GitHub organization following the completion of the Crowd Supply campaign.

According to experts, the commitment to open-source development will allow users to study, modify, and extend the platform, fostering a community-driven ecosystem around the robot and enabling innovations in affordable quadruped robotics.

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Chinese robotics company UBTECH has launched UWORLD, a new consumer-focused brand, along with its U1 series of humanoid robots.

The move marks the company’s expansion from industrial automation into the home robotics market.

UBTECH spent years developing full-size humanoids for factories and warehouses, where manufacturers including NIO and FAW-Volkswagen have used its robots.

The U1 series brings technologies developed for safe human interaction, precision work, and autonomous operation in complex industrial environments into everyday household settings.

In March 2025, UBTECH and Siemens partnered to accelerate humanoid robot production, targeting an annual manufacturing capacity of 10,000 units by 2026.

Lifelike humanoid robots surge

The Shenzhen-based robotics firm recently unveiled the U1 series under its newly created consumer brand, UWORLD. The new series represents a dramatic departure from UBTECH’s traditional focus on industrial humanoid robots deployed in factories and warehouses.

Although the lifelike androids are expected to cost around $30,000, interest has been high. Pre-orders opened on JD.com on June 2, requiring a 3,000 yuan (about $450) deposit, and the company reported more than 2,100 reservations within the first week. Early customers are expected to receive deliveries beginning in mid-September, while a full public launch event is scheduled for June 30, reports Gazgoo.

Over the past several years, the company has supplied advanced humanoid systems for major manufacturers, including Airbus, Texas Instruments, NIO, ZEEKR, Dongfeng Liuzhou Motor, and FAW-Volkswagen. The technologies developed for those demanding industrial environments now form the foundation of the company’s first consumer-oriented humanoids.

UBTECH is offering both male and female versions of the U1. The male model stands 183 centimeters (6 feet) tall, while the female version measures 168 centimeters (5 feet 6 inches). Both feature lifelike silicone skin, realistic hair, expressive facial features, and an impressive 88 degrees of freedom throughout the body. This allows coordinated movement of the arms, legs, hands, neck, chest, and torso, creating highly natural-looking motions, reports Techeblog.

Promotional videos released by the company showcase the robots in cinematic settings, highlighting their realistic appearance. Close-up shots reveal detailed skin textures, natural-looking hair, subtle facial expressions, and reflective eyes designed to enhance their humanlike presence.

UBTECH claims to experience strong early demand for its new line of ultra-realistic humanoid companions, marking a major expansion beyond the industrial robotics market that helped establish the company’s reputation.

Beyond factory bots

Rather than focusing on physical labor, the U1 series is designed primarily for social interaction and emotional companionship.

The robots use onboard artificial intelligence to maintain conversations, recognize moods, and adapt their responses to users. According to UBTECH, the system can analyze facial expressions, tone of voice, and speaking patterns to estimate emotional states and adjust conversations accordingly. When users appear stressed or unhappy, the robot can offer supportive dialogue or attempt to guide interactions in a more positive direction.

The company also emphasizes privacy. Personal memories and conversation data are stored locally with encryption, and owners can customize both the appearance and personality traits of their robot over time. However, UBTECH has deliberately limited the platform’s capabilities. The robots can sit, stand, walk on flat indoor surfaces, and engage in conversation. Still, they are not intended to perform household chores or navigate challenging environments such as stairs or uneven terrain. Users also cannot freely program new behaviors or functions.

UBTECH’s move into consumer robotics is backed by growing momentum in its humanoid robot business. The company reported that revenue from its full-size embodied intelligent humanoid robot products and solutions reached 821 million yuan in 2025, more than 22 times higher than the previous year. The segment accounted for 41.1 percent of total company revenue, up from just 2.7 percent a year earlier, while cumulative deliveries reached 1,079 units, reports Gazgoo.

According to reports, by leveraging technologies originally developed for industrial automation, UBTECH is betting that realistic humanoid companions could become the next major category in consumer robotics.

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A lidar technology company and a robotics AI developer have announced a collaboration to improve how general-purpose robots perceive and navigate complex environments.

The partnership between San Francisco-based Ouster and California -based FieldAI combines high-resolution lidar technology with a universal robot intelligence platform designed to operate across different robot types, tasks, and environments.

The system enables robots to be deployed at new sites without prior maps, pre-planned routes, supporting infrastructure, or environmental modifications.

“Scaling autonomous systems in demanding real-world conditions starts with advanced sensor technology,” said Andrew Mullen, Head of Hardware at FieldAI, in a statement.

Robots gain perception

The collaboration between Ouster and FieldAI aims to accelerate the deployment of autonomous robots in some of the world’s most challenging industrial environments by combining advanced sensing hardware with general-purpose robot intelligence.

The partnership centers on the integration of Ouster’s Rev8 native color digital lidar technology with FieldAI’s Field Foundation Models, a robotics AI platform designed to enable autonomous operation across a wide range of robot types, tasks, and environments. The companies believe the combination can help robots perform reliably in complex, unstructured settings where traditional automation systems often struggle.

FieldAI has developed what it describes as a universal robot “brain” capable of operating across radically different robotic platforms. Unlike conventional robotic systems that typically require detailed maps, carefully planned routes, specialized infrastructure, or extensive site preparation, FieldAI’s technology is designed to allow robots to enter a new worksite much like a newly hired employee. The robots can assess unfamiliar surroundings, understand environmental conditions, and begin operating without prior knowledge of the location.

At the core of this capability are the company’s Field Foundation Models, large-scale AI models trained to understand and interact with the physical world. These models are intended to help robots navigate unpredictable environments where terrain, obstacles, equipment, and working conditions can change continuously. Such environments include construction sites, mines, industrial facilities, energy infrastructure, and remote operational areas where conventional robotic systems often face significant limitations.

To support these capabilities, FieldAI relies on Ouster’s digital lidar sensors, which provide a detailed three-dimensional perception of the surrounding environment. Lidar technology uses laser pulses to measure distances and generate highly accurate spatial maps. Ouster’s latest Rev8 platform adds native color perception to lidar data, enabling robots to capture richer environmental information while maintaining precise depth sensing.

Scaling physical AI

The Rev8 digital lidar platform is designed to deliver high-resolution perception in conditions where cameras or GPS-based systems may be less effective.

According to its developers, it is particularly important in unmapped environments, indoor facilities, underground operations, and GPS-denied locations where autonomous systems must rely heavily on onboard sensing. The technology’s rugged construction also makes it suitable for deployment in harsh industrial conditions involving dust, vibration, weather exposure, and heavy machinery.

FieldAI already uses Ouster’s lidar technology to support navigation and autonomy in complex operational settings. As the company expands deployments with major industrial customers, it plans to incorporate the enhanced sensing capabilities of the Rev8 platform to further improve robot safety, environmental awareness, and decision-making. The addition of native color data is expected to provide greater interpretability of robot actions and improve the ability of autonomous systems to identify and understand objects and conditions in their surroundings.

The collaboration is expected to support the broader adoption of physical AI systems across industries where labor-intensive, hazardous, or difficult-to-access tasks remain challenging for human workers. Target sectors include construction, mining, energy production, manufacturing, security operations, and government applications.

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London-based startup morph has launched a new soft robotics platform designed to bring physical intelligence directly into products through adaptive, deformable materials.

Founded by a former reconstructive surgeon, the company says its “soft robotic cells” combine embedded sensing and adaptive control to enable real-time changes in shape and stiffness.

The technology is aimed at creating products that can sense, adapt, and respond to human interaction, marking a shift from traditional static systems to responsive, AI-enabled physical solutions for consumer and enterprise applications.

“With our platform, we can build a new generation of products embedded with soft robotic cells that adapt in real time to support natural movement,” said Dr. Jean Nehme, Founder of morph, in a statement.

A soft robotics platform

The UK startup has unveiled what it describes as the world’s first soft robotics platform, introducing a new approach to physical AI through adaptive, deformable robotic materials.

Founded by London-based Dr. Jean Nehme, a former reconstructive surgeon and founder of surgical AI company Digital Surgery, morph is developing “soft robotic cells” — modular robotic units made from synthetic materials that can sense, process information, and physically adapt to changing conditions.

Unlike traditional robots built from rigid components and designed primarily for industrial environments, soft robots are constructed from flexible materials that allow safer and more natural interaction with people.

The company’s technology enables robotic cells to alter their shape and stiffness in real time in response to environmental conditions and user needs. By embedding sensing, adaptive control, and intelligence directly into materials, morph aims to create products that can actively respond to human movement and interaction rather than remain static. The approach represents a shift toward embodied AI, where intelligence is integrated into physical systems capable of taking action through the product itself.

According to morph, these soft robotic cells can be combined and configured across a range of products, generating data that supports richer interactions between humans and the physical world. The platform is designed to serve as a foundation for multiple industries, allowing manufacturers to integrate adaptive robotic capabilities into their own products.

Future mobility reimagined

Morph’s initial applications will focus on human performance, mobility, and longevity. Early products are being developed for athletic performance enhancement, injury prevention, and mobility support. The company believes its technology could eventually expand into healthcare, automotive, and industrial safety sectors, where adaptive materials could improve comfort, safety, and functionality.

Inspired by the adaptability of octopuses, morph has built a development platform that allows engineers to program robotic cell behaviors, simulate real-world environments, and rapidly prototype deformable components intended for direct human interaction. The system combines reinforcement learning with high-fidelity physics-based simulations, helping accelerate the transition from concept to deployable product while maintaining safety and reliability standards.

The company is currently working with several industrial partners and plans to operate primarily as a software, design, and fabrication partner for businesses seeking to adopt soft robotics technology. Through its business-to-business strategy, morph aims to help companies incorporate adaptive robotic materials into future products.

“Driven by a worldwide team of experts in robotics, AI, medicine, design, and manufacturing, morph enables the creation of products that embed robotic cells. Initial product offerings will focus on human performance and longevity,” claims the firm in a statement.

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