Katalyst Space’s LINK robotic servicing satellite awaits encapsulation inside a Northrop Grumman Pegasus XL on June 8, 2026, at NASA’s Wallops Flight Facility in Virginia. The rocket will carry LINK to space for an attempted orbital boost of NASA’s Neil Gehrels Swift Observatory.
NASA/Ron Beard
Engineers completed installation of Katalyst Space’s LINK robotic servicing spacecraft into a Northrop Grumman Pegasus XL rocket on Tuesday, June 9, at NASA’s Wallops Flight Facility in Virginia. Launch is anticipated later this month.
Our planet’s atmosphere creates drag for spacecraft in low Earth orbit, gradually reducing their altitudes if they don’t have propulsion systems to counteract the effect.
Recent solar activity magnified this effect on Swift, and its orbit decayed faster than anticipated.
Katalyst’s Hunter Robertson prepares LINK ahead of it being attached to the Pegasus XL inside the Horizontal Integration Facility at NASA Wallops on June 6, 2026.
NASA/Ron Beard
Based on the orbital and programmatic needs of the mission, Katalyst selected the air-launched Pegasus XL as the best means of reaching the observatory in time to perform the boost maneuver.
Northrop Grumman will launch the rocket using Stargazer, its modified L-1011 aircraft.
Next, Northrop Grumman engineers will attach Pegasus XL to Stargazer, which will carry it from NASA Wallops to Kwajalein Atoll, part of the Republic of the Marshall Islands in the South Pacific Ocean, for launch.
KAIST researchers solved a key challenge in the commercialization of physical AI by developing a new technology that enables AI to learn human judgment criteria on its own from just a few videos.
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.
German industrial giant Bosch said Wednesday it will step up efforts in the field of humanoid robotics as its traditional auto parts business comes under increasing pressure.
In a landmark achievement for robotics, a bicycle-riding robot has performed the world’s first unassisted front flip, astonishing engineers and robotics enthusiasts alike. The feat, accomplished by a team at the University of Tokyo’s JSK Robotics Laboratory, marks a significant leap in the capabilities of autonomous machines and could have far-reaching implications for robotics research, mobility, and future transportation.
Engineering a robotic stunt rider
The robot, dubbed “Rider-Bot,” is built to mimic the movements and balance strategies of human cyclists. Unlike previous robotic stunts that required ramps, wires, or external supports, Rider-Bot executed the front flip entirely on its own—using only its onboard sensors, actuators, and algorithms.
The successful flip took place on a flat surface, with the robot accelerating, launching, rotating 360 degrees forward, and landing upright—all without human intervention.
According to the research team, achieving this level of acrobatic control required a combination of advanced gyroscopes, real-time feedback loops, and machine learning techniques. “This is a major step toward robots that can adapt dynamically to complex environments and perform tasks that were previously considered impossible for machines,” said Dr. Yuta Sato, lead researcher on the project.
Implications for robotics and beyond
The successful front flip demonstrates not only the mechanical resilience of Rider-Bot but also the sophistication of its AI-driven decision-making. The robot’s control system anticipates and compensates for shifts in momentum and balance, much like a skilled human cyclist would.
Researchers believe this breakthrough could inform the design of next-generation delivery robots, autonomous vehicles, and even disaster-response machines capable of navigating unpredictable terrain. “Our work shows that robots can be taught to handle extreme maneuvers, which opens up many possibilities for robust, adaptable mobility in real-world scenarios,” Dr. Sato noted.
Challenges and next steps
Despite the successful demonstration, the team acknowledges ongoing challenges. Perfecting the landing and ensuring consistency across different environments remain top priorities. The researchers plan to enhance the robot’s learning algorithms and test it in outdoor and obstacle-rich settings.
The team also hopes their achievement will inspire further research into dynamic locomotion and the integration of robotics into everyday life. “We’re just beginning to scratch the surface of what intelligent, mobile robots can do,” said Dr. Sato.
A milestone for human-robot collaboration
The Rider-Bot’s unassisted front flip not only pushes the boundaries of robotics but also highlights the growing intersection between human athleticism and machine intelligence. As robots become more capable of complex movement, their potential roles in society—from urban mobility to emergency response—are poised to expand dramatically.
With this record-breaking feat, the University of Tokyo’s robotics team has set a new benchmark for autonomous machines, paving the way for future innovations in robotic agility and intelligence.
A bicycle robot from the Robotics and AI Institute (RAI) in Cambridge, Massachusetts, has become the first to perform an unassisted acrobatic front flip. RAI calls the bicycle robot an ultra-mobility vehicle (UMV). It can reach a height of 3 feet (0.9 meters) and can jump from the floor onto a platform. The contributions of a Georgia Tech Ph.D. student helped make these feats possible through a robot control policy he developed.
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.
Cornell researchers are investigating the potential for using artificial intelligence to give robots social intelligence—the ability to read facial cues, anticipate the needs of those around them, and function within society. The new study tested the ability of vision language models (VLMs)—AI systems that can interpret and generate both visual information and language—to predict whether a tense scenario in a short video would end well or badly, such as a toddler carrying an overly full mug of coffee.
Anthropic has opened the doors to its most advanced AI system yet, but not without placing guardrails around its most sensitive capabilities.
The company on Tuesday unveiled Claude Fable 5, the first publicly accessible version of its Mythos-class AI model. Anthropic says the model outperforms every generally available system it has released to date, delivering major gains in software development, analytical work, visual understanding, and scientific reasoning.
The launch marks a significant shift for the AI firm. Until now, Mythos-level capabilities remained restricted to a small group of trusted organizations because of concerns that the technology could aid cyberattacks and other harmful activities. Fable 5 changes that equation by bringing those capabilities to a broader audience while routing certain high-risk requests through a less permissive model.
Safety before scale
Anthropic said Fable 5 includes a new layer of AI-powered classifiers designed to detect potentially dangerous prompts and jailbreak attempts. The company stress-tested those safeguards before releasing the model to the public.
If users submit requests involving cybersecurity, biology, chemistry, or model distillation, the system automatically redirects those interactions to Claude Opus 4.8 instead of Fable 5. Users receive a notification whenever that fallback occurs, allowing them to understand why the switch happened.
Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.
Its capabilities exceed those of any model we’ve ever made generally available. pic.twitter.com/2AvmEjHIX8
The company acknowledged that the safeguards may occasionally block harmless requests. However, Anthropic said early testing showed that fewer than 5% of sessions triggered a fallback response. “We’ve deliberately tuned the safeguards to be cautious,” the company said, adding that it plans to refine the system over time to reduce unnecessary interventions.
Built for demanding work
Anthropic argues that Fable 5 delivers its biggest advantages when tackling lengthy and complex assignments. The company says the model can stay focused across extended workflows while maintaining consistency over large amounts of context.
During early evaluations, payments company Stripe reported that the model completed a large-scale migration across a 50-million-line Ruby codebase in roughly one day. According to Anthropic, the same task would have otherwise occupied an engineering team for more than two months.
The company also highlighted gains in financial analysis. On Hebbia’s finance benchmark, Fable 5 posted the strongest results among leading models. Trading firm IMC found that the system performed well across factual analysis, reasoning tasks, root-cause investigations, and expected-value calculations.
Fable 5 also advanced Anthropic’s vision capabilities. The model can extract detailed information from scientific figures and reconstruct web applications from screenshots. In another demonstration, it completed Pokémon FireRed using a minimal vision-only setup after earlier Claude models struggled with the challenge.
Mythos stays restricted
Alongside Fable 5, Anthropic introduced Claude Mythos 5, a version of the same underlying model with fewer restrictions in select areas. Anthropic says the model offers the strongest cybersecurity capabilities it has developed so far.
Access to Mythos 5 remains limited. The company is deploying it through Project Glasswing while expanding availability to approved cyber defenders and organizations responsible for critical infrastructure. Anthropic said it intends to broaden access further through a trusted program in the future.
Fable 5 is available through Anthropic’s Claude API and consumption-based Enterprise offerings. Through June 22, Pro, Max, Team, and seat-based Enterprise subscribers can access the model at no additional cost. After that date, Anthropic plans to move users to a credit-based system before eventually restoring broader subscription access.
As competition intensifies across the AI industry, Anthropic is betting that powerful models do not have to arrive without safeguards. With Fable 5, the company is testing whether frontier capabilities and tighter controls can coexist in the hands of everyday users.
Humanoid robots struggling with tasks like grasping a cup have a new teacher—a person wearing an ultrasound wristband that captures the movement of muscles, tendons and ligaments beneath the skin.
Scientists from ETH Zurich in Switzerland have announced a series of successful experiments involving the repair of injured spinal cords in zebrafish and mice after being injected with magnetically controlled microrobots containing pluripotent stem cells.
According to a statement announcing the ETH team’s work, both the zebrafish and mice injected with the microrobots showed improved movement and normalized exploratory behavior within just a few days after treatment.
Although the initial studies were confined to lab animals, the team hopes their magnetically controlled microrobot approach to the precision delivery of pluripotent stem cells could eventually be adapted for humans with spinal cord injuries.
Spinal Cord Repair Microrobots Treat Nerve Cells That Resist Regeneration
Unlike some cells in the human body, nerve cells within the spinal cord rarely regenerate on their own. If the spinal cord is injured, scarring can further reduce the ability of the nerve fibers within the cord to regrow. For people living with spinal cord injuries, this scenario can offer a bleak prognosis for recovery.
In recent decades, scientists have turned to the natural regenerative properties of pluripotent stem cells. Although the use of stem cells was initially controversial due to the need to extract neonatal stem cells, scientists ultimately learned to convert ordinary stem cells into pluripotent stem cells capable of becoming any cell type in the human body.
The most promising approach involves implanting stem cells at the site of the injury and then using electrical stimulation to promote the growth of new cells. However, according to the ETH team behind the new approach, the current method has several drawbacks.
First, stimulating the cells requires the use of implanted electrodes. Second, the team notes that after transplantation, many of the stem cells “do not always survive or integrate properly into the existing tissue.”
To improve healing and increase the chance of restoring spinal cord nerve cell function, they said their new approach combines therapeutic stem cells with magnetoelectric nanoparticles and uses magnetic fields to guide them to the “precise site of an injury” and “stimulate the stem cells to accelerate repair.”
NPCbots Combine Stem Cells and Magnetically Controlled Nanoparticles
To construct their magnetically guided spinal cord repairing robot, the team built what they termed a “biohybrid microrobot.”
First, the team creates pluripotent stem cells from adult cells by genetically manipulating them in the lab. The result is what researchers call an “induced” pluripotent stem cell (iPS). According to the study authors, these newly pluripotent iPS cells are used to derive living neural progenitor cells (NPCs), meaning “they have the potential to differentiate into various types of nervous system cells.”
Next, the team creates customized magnetic nanoparticles consisting of two layers. The inner layer responds to the “commands” from the magnetic fields used to control them, and an outer layer that converts this response into an electrical signal.
According to Professor Salvador Pané i Vidal of the Multi-Scale Robotics Lab at ETH Zurich, each tiny robot has a reservoir near the center “where we trap the cells.” The professor said the best way to accomplish this is to inject the nanoparticles into a solution with the NPC, “and wait for the two components to bind.”
After 30 minutes, the process is complete, and the team is left with a batch of nanobots, each around 6 micrometers in size. Since the new robots combine a magnetic bot and a reservoir of NPCs, the team named them ‘NPCbots.’
In preparatory cellular experiments, the researchers used hundreds of thousands of NPCbots. However, several million were required for animal trials.
Zebrafish and Mice Regain Movement After Injections
To test the efficacy of their new NPCbots, the ETH team injected millions of them into the spinal cord of zebrafish larvae with spinal cord injuries. To improve the chances of nerve regeneration, the NPCbots were injected directly into the site of the injury.
After injecting the microrobots, the injury site was subjected to electromagnetic fields. Although the repair was not immediately evident, the team noted that after three days, the zebrafish with the injured spinal cords “exhibited nearly normal swimming and exploratory behaviour.”
At the start and after three days: the top images show the uninjured spinal cord of a zebrafish; those in the middle show the injured spinal cord; and those at the bottom illustrate how the nerve cells grow thanks to the microrobots. Image Credit: ETH Zurich.
Next, the team injected millions of NPCbots into mice with completely separated spinal cords. According to the team, the results were “very promising.”
“After 28 days, the animals’ nerve cells had reconnected at the site of the injury,” they explained.
The team said further observation of the treated mice revealed “increasingly normal movement patterns,” including improvements in gait, stride length, and coordination. The ETH team also noted that the mice’s exploratory behavior “improved significantly.”
Schematic illustration of nerve cell recovery in zebrafish and mice. Image Credit: ETH Zurich.
When discussing the mouse experiments, the team described the result as “particularly significant” because zebrafish spinal cords regenerate, whereas mouse spinal cords do not. They also noted that the treatment was “well tolerated by the animals,” with no reported immune reactions or adverse effects.
Minimally Invasive and More Precise Treatments with Microbots
Unlike science fiction movies, where tiny robots repair tissue mechanically, the research team said that the stem cells carried by the NPCbots are exposed to electrical stimulation, “greatly enhancing their differentiation after transplantation.” This means the nanoparticles convert the electric signals from the EM field into electrical impulses, stimulating healing.
Unlike more complicated stem cell procedures that use implanted electrodes and cables, the team said they only needed to apply external magnetic fields around the spinal cord injury site. The team said this simplification was “crucial,” since the spinal cord is considered extremely sensitive. They also note that the ability to manipulate the frequency and field strength of magnetic fields, combined with their ability to penetrate deeply into tissue, makes the entire process safe and easy to control.
“Microrobotic guidance makes the treatment more precise and minimally invasive,” Hao explained.
After the NPC bots have delivered and stimulated the stem cells, the team said they “essentially dissolve” within the tissue. Because the bots contain a barium titanate coating, the researchers also believe that they will be “stable and minimally reactive” with surrounding tissue. Still, they concede that “further studies will determine whether and how the particles are degraded or excreted over the long term.”
Expanding NPCbot Therapies to Increase the Effectiveness of Other Targeted Therapies
Although the team described the animal trials of their NPCbots as “promising,” they noted that further research is needed before the process can be attempted on human patients with spinal cord injuries. For example, Hao noted that in addition to ‘clinical aspects’ that require more exploration, the team needs to start by determining which magnetic fields “work best in humans” and determining the “optimal stimulation duration” for human NPCs. Nevertheless, the team noted, they are “already considering further applications.”
“The reproducible and scalable production of microrobots using our lab-on-a-chip system demonstrates that the platform’s application potential extends beyond basic research,” Professor Vidal explained.
Some potential biomedical applications mentioned by the RETH team include cardiology, oncology, wound healing, “and other targeted therapies,” adding that their process could make such treatments “safer, more controllable and more effective.”
Christopher Plain is a Science Fiction and Fantasy novelist and Head Science Writer at The Debrief. Follow and connect with him on X, learn about his books at plainfiction.com, or email him directly at christopher@thedebrief.org.
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Human hands exhibit unparalleled complexity and dexterity, revealing the mastery of their Creator. Despite advancements in robotics, replicating the nuanced movements and strength of human hands remains a significant challenge. Companies like Proception are striving to develop robotic hands, yet authentic human hand functionality remains unmatched, highlighting the intricacies of divine design.
Intel is invading the physical AI space with a reentry into the robotics market it quit many years ago amid financial struggles.
The robotics strategy is part of the company’s larger plan to establish AI on the “edge,” in which devices have the computing capability to run AI locally. Many devices lack AI capabilities and have to offload processing to the cloud.
The chipmaker said its Intel Series 3 processors are now in 130 edge AI and robotics designs. It also had a design win with SensoryAI, which provides technology for robots that include Ella, a robotic barista made by Crown Digital.
The company’s Core Ultra Series 3 processors are derivatives of chip designs intended for laptops. But Intel has achieved a level of power efficiency for long battery life that allows those chips to be adapted for handheld devices and laptops.
Intel also said it can build advanced robotics chips thanks to its latest manufacturing technologies.
For example, many robotic functions, such as computer vision and real-time controls, can be integrated into a single chip. Previously, functions like graphics and movement and control were distributed among different cores in a chip.
SensoryAI, for example, has a chip architecture that provides the robotic barista — which is more like a robotic arm — with AI capabilities, Intel said.
The main “Avatar” agent handles customers as the main “Ella” agent reasons and executes the task. If Ella encounters errors, it passes on the issue to a Guardian agent, which helps with the recovery. Some issues could include making sense of an order, or cups that might be stuck.
The three agents are embedded in a single piece of Core Ultra Series 3 silicon.
Intel is displaying some of those robots at the Computex trade show in Taiwan. The company shared a video of a humanoid-style robot from the floor in a X.com post
This is not Intel’s first attempt at the robotics market. Intel sold robotics chips and kits when it was a dominant chip player in the field, but curtailed efforts in 2021 after Pat Gelsinger took over as CEO and restructured the company to focus on manufacturing.
Robotics is now back on the menu under new Intel CEO Lip-Bu Tan, who replaced Gelsinger last year. He has restructured to company to focus on high-growth areas that can generate high returns.
A Morgan Stanley study last year indicated the robotics market could be worth $5 trillion by 2050 — and more than 1 billion humanoid robots could be in operation.
However, challenges remain. There isn’t yet enough real-world data to train robots to do targeted work. And the AI models — generally called world models — they will need are still under development.
Training robots to do a specific job requires a sequence of events to happen in succession without any errors. Companies are still training robots to spot and understand errors, analyze possible resolutions, and take the right corrective action.
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