Articles tagged with "physical-AI"
New frontiers in robotics at CES 2026 - Robohub
At CES 2026, physical AI—embodied intelligence manifested as robots—emerged as a dominant theme, signaling a shift from experimental lab research to consumer technology. The event showcased how robotics is increasingly integrated into everyday products, with major brands beyond traditional robotics companies embracing this trend. Although the consumer robotics on display may not match cutting-edge academic research in sophistication, they represent innovation driven by consumer needs and manufacturability. The scale and diversity of the show highlighted the growing commercial and public interest in robotics, particularly humanoid robots. Humanoids were a central focus at CES 2026, reflecting their rise as a major trend in robotics. Exhibitors ranged from Booster, which offered child-sized humanoid robots designed for educational purposes and already achieving strong sales at $10,000 each, to Unitree, which impressed audiences with agile humanoid robots capable of boxing, dancing, and acrobatics. Unitree’s advancements leveraged improved actuators and reinforcement learning to enhance adaptability and performance. Meanwhile
roboticsphysical-AIhumanoid-robotsCES-2026consumer-technologyrobotics-innovationautonomous-systemsChina's LimX Dynamics raises funds to build humanoid robot 'brains'
Chinese robotics company LimX Dynamics has secured approximately $200 million in Series B funding to advance its development of embodied intelligence in humanoid robots. The funding round included investors such as UAE-based Stone Venture, Oriental Fortune Capital, JD.com, and others. LimX Dynamics focuses on integrating AI with physical machines, enabling robots to learn and adapt through interaction with their environment—a concept known as embodied intelligence, which is a subset of Physical AI. The company has developed two core technologies: COSA (Cognitive OS of Agents), a software platform serving as the robot’s “brain” that controls whole-body motion, and Tron 2, a modular hardware system for building humanoid robots. COSA functions similarly to the human cerebellum, enabling fluid, coordinated movements and real-time task reprioritization without human intervention. Their humanoid robot, Oli, stands 5 ft 4 in tall, weighs 121 pounds, and features dual arms with seven degrees of freedom, capable of handling objects up
roboticshumanoid-robotsAIembodied-intelligencemodular-roboticsautonomous-robotsphysical-AIGerman industrial humanoid robot Agile One offers precise hand skills
German startup Agile Robots has introduced Agile One, a humanoid robot designed to enhance industrial productivity through advanced Physical AI and human-like dexterity. Equipped with 71 degrees of freedom—including 21 in each hand—Agile One features sensor-rich, tactile fingertips and force-torque sensing at every joint, enabling it to perform delicate and forceful tasks with high precision and stability. Standing 174 cm tall and weighing 69 kg, the robot can carry payloads up to 20 kg, move at speeds up to 2.0 m/s, and operate for up to eight hours on a single battery charge. Its onboard AI supports audio-based interaction and spatial awareness, allowing it to navigate dynamic factory environments and collaborate safely and intuitively with human workers. Agile One is designed for complex, repetitive, and high-precision industrial tasks such as material transport, machine tending, tool use, and precise manipulation. The robot’s AI is trained on one of Europe’s largest industrial datasets, supplemented by simulations
robothumanoid-robotindustrial-automationAI-roboticsdexterous-robot-handsfactory-roboticsphysical-AITechCrunch Mobility: ‘Physical AI’ enters the hype machine
The article from TechCrunch Mobility highlights the growing prominence of "physical AI" or "embodied AI" showcased at the 2026 Consumer Electronics Show (CES) in Las Vegas. With traditional U.S. automakers notably absent, the event was dominated by autonomous vehicle technology firms, Chinese automakers, and companies specializing in AI-driven robotics and automotive chips. Physical AI refers to AI systems integrated with sensors, cameras, and motor controls that enable machines—such as humanoid robots, drones, and autonomous vehicles—to perceive and interact with the physical world. Hyundai, for example, featured a range of robots, including those from its subsidiary Boston Dynamics, and innovations like an autonomous vehicle charging robot and a four-wheel electric platform called Mobile Eccentric Droid (MobEd), set for production in 2026. The enthusiasm around humanoid robots was significant, with industry leaders like Mobileye’s Amnon Shashua acknowledging the hype but affirming the long-term reality and potential of humanoid robotics despite
robotautonomous-vehiclesphysical-AIembodied-AIroboticselectric-vehiclessensorsVideo: First-ever live unscripted conversation between humanoid robots
At CES 2026, Realbotix showcased a pioneering demonstration featuring two humanoid robots, Aria and David, engaging in the first-ever fully autonomous, unscripted conversation between physical humanoid robots. The dialogue lasted over two hours in real time without any human intervention, scripting, or teleoperation. Both robots operated using Realbotix’s proprietary AI software running entirely on-device, emphasizing a concept the company calls “physical AI,” where embodied systems perceive, respond, and adapt to each other dynamically rather than following pre-programmed scripts. The conversation was multilingual, spanning English, Spanish, French, and German, highlighting the flexibility of Realbotix’s language models and embodied AI platform. While the interaction demonstrated significant progress in autonomous humanoid communication, observers noted limitations such as noticeable pauses, speech inconsistencies, and mechanical delivery lacking the fluidity and expressiveness seen in other advanced humanoid robots like Ameca. Visually, the robots appeared more like “rubber mannequins with speakers
robothumanoid-robotsAIphysical-AIon-device-AImultilingual-AIRealbotixInside CES 2026’s “physical AI” takeover
At CES 2026, a significant shift in artificial intelligence was on full display as AI moved beyond digital interfaces like chatbots and image generators into the physical world. The event in Las Vegas was dominated by “physical AI” innovations and robotics, showcasing technologies such as Boston Dynamics’ redesigned Atlas humanoid robot and AI-powered devices including ice makers. This transition highlights AI’s expanding capabilities, demonstrating that it can now perform complex physical tasks like moving car parts in factories, capturing drones with net guns, and even entertaining through dance performances at automaker booths. The presence of these advanced AI-driven machines at CES 2026 signals a broader industry push to integrate AI into tangible, real-world applications, emphasizing its readiness to impact various sectors beyond traditional software roles. The coverage by TechCrunch’s Equity podcast further explores these developments and related industry deals, underscoring the growing importance of physical AI in technology innovation. The article also briefly introduces Theresa Loconsolo, an audio producer at TechCrunch, who contributes to
robotphysical-AICES-2026Boston-DynamicsAtlas-robotAI-roboticsautomationAMD hardware-powered humanoid robot uses body as computing system
Italian robotics company Generative Bionics unveiled its humanoid robot concept, GENE.01, at CES 2026. Scheduled for commercial launch in late 2026, GENE.01 is designed around the principle of Physical AI, using its entire body as a computing system. The robot features a full-body tactile skin embedded with a distributed network of touch and force sensors, enabling it to sense contact, pressure, and subtle physical interactions. This tactile input is integrated into its core decision-making processes, allowing real-time responses to human touch or collisions, thereby facilitating safer and more natural human-robot interactions. Powered by AMD’s suite of CPUs, GPUs, embedded processors, and FPGA-based systems, GENE.01 processes sensory data locally near the sensors rather than relying on a centralized brain. This distributed computing approach enables split-second reactions and smoother movements, reflecting an efficiency inspired by human intelligence residing both in the brain and body. Generative Bionics emphasizes openness by leveraging AMD-supported open-source
roboticshumanoid-robotphysical-AItactile-sensorsAMD-processorsindustrial-automationAI-computingCES 2026: NVIDIA launches Alpamayo 1 for autonomous vehicles
At CES 2026, NVIDIA announced a significant expansion of its open AI ecosystem, unveiling new models, datasets, and development tools aimed at advancing AI applications beyond digital tasks into physical environments such as autonomous vehicles, robotics, and biomedical research. Central to the announcement was the introduction of Alpamayo, a family of open models and tools for reasoning-based autonomous driving. Alpamayo 1, an open vision language action model, enables vehicles to perceive their surroundings and explain their decisions. Complementing this, NVIDIA launched AlpaSim, an open-source simulation framework for training and evaluating autonomous systems, along with Physical AI Open Datasets containing over 1,700 hours of diverse driving data. NVIDIA’s expanded portfolio also includes open models across multiple domains: Nemotron for agentic AI, Cosmos for physical AI, Isaac GR00T for robotics, and Clara for healthcare and life sciences. The company released extensive datasets, including 10 trillion language tokens, 500,000 robotics trajectories, 455
roboticsautonomous-vehiclesAIsimulation-toolsphysical-AINVIDIAopen-datasetsNew physical AI lets EVs detect loss of control in real time
Researchers led by Professor Kanghyun Nam at DGIST, in collaboration with Shanghai Jiao Tong University and the University of Tokyo, have developed a novel physical AI-based system to improve real-time vehicle state estimation for electric vehicles (EVs). This system addresses the critical challenge of accurately detecting vehicle motion states—especially the sideslip angle, which indicates sideways sliding during turns or low-friction conditions and is vital for vehicle stability. Traditional models struggle with unpredictable real-world factors like tire deformation and varying road surfaces, but the new hybrid framework combines physical tire models with AI-driven regression to adapt dynamically to these nonlinear behaviors. At the core of the system is an unscented Kalman filter observer integrated with Gaussian process regression, which together ensure both physical consistency and learning flexibility. Tested on an actual EV platform across diverse road conditions and speeds, the system demonstrated strong accuracy and robustness. This advancement enables earlier and more precise interventions by stability control and autonomous driving systems, enhancing safety and energy efficiency. Professor Nam emphasized that
robotartificial-intelligenceelectric-vehiclesautonomous-drivingvehicle-stabilitysensor-technologyphysical-AIKorea’s POSCO invests in US industrial humanoid robot firm Persona AI
South Korean steel giant POSCO, through its tech subsidiary POSCO DX, is investing a total of $3 million in US-based industrial humanoid robot startup Persona AI, which is led by former NASA and Figure AI engineers. POSCO DX aims to leverage this investment to develop humanoid robots capable of replacing high-risk manual labor at its industrial sites, integrating the group’s AI technology with robotics to create “Physical AI”—machines with built-in intelligence designed to operate safely and effectively in real-world industrial environments. This initiative aligns with POSCO’s broader goal to enhance workplace safety and reduce industrial accidents through automation. Persona AI specializes in building humanoid robots tailored for heavy-duty industries such as shipbuilding, energy, mining, and construction. Unlike general-purpose robotics firms, Persona AI focuses on environments requiring human-like dexterity and adaptability, equipping its robots with advanced touch sensors and AI algorithms that enable precise, autonomous task execution. These robots are designed to work collaboratively with human supervisors and coworkers, addressing labor shortages
robothumanoid-robotsindustrial-automationAI-roboticsmanufacturing-technologyPOSCOphysical-AIEY rolls out physical AI platform, opens EY.ai Lab, and names global robotics lead - The Robot Report
EY, the global consultancy under Ernst & Young Global Ltd., is expanding into physical AI and robotics through a new AI platform, leadership appointment, and the launch of the EY.ai Lab. The company emphasizes the critical importance of high-quality, accessible, and scalable “AI-ready” data as foundational for successful physical AI applications. Joe Depa, EY’s global chief innovation officer, highlighted that without addressing data challenges such as quality, accessibility, and scarcity, robotic systems will fail to perform effectively. EY leverages its extensive experience managing vast financial datasets—processing over 1 trillion lines annually and handling 1.6TB+ weekly of AI-ready data products—to support this initiative. EY’s physical AI platform, developed in collaboration with NVIDIA using Omniverse libraries, NVIDIA Isaac, and NVIDIA AI Enterprise software, aims to cover the entire application lifecycle for AI-driven robots, drones, and smart edge devices. The platform focuses on generating synthetic data for scenario simulation, creating digital twins for realistic 3D robotics
roboticsartificial-intelligencephysical-AINVIDIA-Omniversedigital-twinAI-data-managementAI-governanceSoftBank and Yaskawa to collaborate on physical AI for the office - The Robot Report
SoftBank Corp. and Yaskawa Electric Corp. have announced a collaboration to develop "physical AI" for social and office robotics, combining Yaskawa’s mobile manipulator technology with SoftBank’s AI and connectivity infrastructure. Physical AI is defined as technology enabling robots to analyze sensor and camera data through AI to perform flexible, complex physical tasks and multi-tasking capabilities, moving beyond conventional robots designed for single, specific functions. This initiative aims to address Japan’s demographic challenges, such as a shrinking workforce, by creating robots capable of flexible decision-making in complex environments like offices, hospitals, and schools. The partners have developed an office use case involving a virtual building management system that centrally manages facility data, office supplies, and robot operations. SoftBank provides AI-RAN communications infrastructure, multi-access edge computing (MEC), and a vision-language model (VLM) to generate task instructions, while Yaskawa contributes its MOTOMAN NEXT mobile manipulator and a vision-language-action (VLA)
roboticsartificial-intelligenceoffice-robotsphysical-AIYaskawaSoftBankautomationNvidia announces new open AI models and tools for autonomous driving research
Nvidia has unveiled new AI infrastructure and models aimed at advancing physical AI applications, particularly in robotics and autonomous vehicles. At the NeurIPS AI conference, the company introduced Alpamayo-R1, described as the first vision-language-action model specifically designed for autonomous driving research. This model integrates visual and textual data to enable vehicles to perceive their environment and make informed decisions, leveraging Nvidia’s existing Cosmos reasoning model family, which was initially launched in January 2025. Alpamayo-R1 is intended to help autonomous vehicles achieve level 4 autonomy—full self-driving capability within defined areas and conditions—by providing them with “common sense” reasoning to handle complex driving scenarios more like humans. In addition to the new model, Nvidia released the Cosmos Cookbook on GitHub, a comprehensive resource including step-by-step guides, inference tools, and post-training workflows to assist developers in customizing and training Cosmos models for various applications. This toolkit covers essential processes such as data curation, synthetic data generation, and model
robotautonomous-vehiclesAI-modelsNvidiaphysical-AIautonomous-drivingvision-language-modelsMassRobotics expands physical AI fellowship with AWS and NVIDIA - The Robot Report
MassRobotics, in partnership with Amazon Web Services (AWS) and NVIDIA Inception, has launched applications for the second cohort of its Physical AI Fellowship, an eight-week virtual program designed to help robotics and physical AI startups scale their innovations. The fellowship aims to advance the integration of artificial intelligence with robotics to create smart machines capable of understanding and interacting with the physical world. Selected startups will benefit from access to MassRobotics’ global network, AWS’s AI stack and up to $200,000 in AWS credits, as well as NVIDIA’s robotics software and expert mentorship. The program builds on the success of the inaugural 2025 cohort, where eight startups received tailored technical support to accelerate innovation in areas such as foundation model development, simulation optimization, and edge deployment. These companies worked on diverse applications ranging from autonomous construction equipment and ocean vessels to hospital service robots and robotic exoskeletons. The fellowship partners emphasize that the collaboration helps translate complex AI research into practical robotics solutions that address real-world business challenges
roboticsartificial-intelligencephysical-AIAWSNVIDIAstartupstechnology-innovationWatch: German firm launches new humanoid robot for industrial jobs
Munich-based Agile Robots has introduced Agile ONE, its first humanoid robot designed for industrial environments. Announced on November 19, Agile ONE features five dexterous fingers equipped with fingertip and force-torque sensors, enabling it to perform a wide range of factory tasks such as material handling, pick-and-place, machine tending, and fine manipulation with high precision and adaptability. The robot’s AI is trained on one of Europe’s largest real-world industrial datasets, supplemented by simulated and human-collected data, and employs a layered cognitive architecture that separates strategic planning, rapid response, and fine motor control. This design aims to create a highly adaptive robot capable of safe, collaborative work alongside humans and existing robotic systems. Agile ONE emphasizes human-friendly interaction through features like bright colors, responsive eyes, proximity sensors, and an information display on its chest, prioritizing safety and comfort in robot-human interaction. Full production is slated to begin in early 2026 at Agile Robots’ facility in Bavaria. The
robothumanoid-robotindustrial-automationAI-roboticscollaborative-robotsdexterous-robotic-handsphysical-AISocial media round-up from #IROS2025 - Robohub
The 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025) was held from October 19 to 25, 2025, in Hangzhou, China. The event featured a comprehensive program including plenary and keynote talks, workshops, tutorials, forums, competitions, and debates. An exhibition allowed companies and institutions to showcase their latest robotics hardware and software innovations. Social media coverage highlighted various activities and demonstrations, such as a modular legged wheel design by DirectDriveTech and a live demo of the G1 robot by Unitree Robotics. Notably, 16-year-old Jared K. Lepora was recognized as the youngest presenter, demonstrating a dexterous robotic hand in the Educational and Emotional Robots session. The conference brought together leading experts in robotics, AI, and intelligent systems to explore advancements at the human-robotics frontier. Highlights included discussions on integrating specialist and generalist approaches to physical AI and insights from conference chairs Professor Hesheng Wang and
roboticsintelligent-systemsAIrobotic-handmodular-robotsIROS2025physical-AICoco Robotics taps UCLA professor to lead new physical AI research lab
Coco Robotics, a startup specializing in last-mile delivery robots, has established a new physical AI research lab led by UCLA professor Zhou, who has also joined the company as chief AI scientist. The move aims to leverage the extensive data—spanning millions of miles collected over five years in complex urban environments—to advance autonomous operation of their delivery bots and reduce delivery costs. Coco Robotics co-founder and CEO Zach Rash emphasized that the company now has sufficient data scale to accelerate research in physical AI, particularly in robot navigation and reinforcement learning, areas where Zhou is a leading expert. The new research lab operates independently from Coco Robotics’ partnership with OpenAI, which provides access to language models, while the lab focuses on utilizing the company’s proprietary robot-collected data. Coco Robotics plans to use the insights gained exclusively to enhance its own automation capabilities and improve the efficiency of its local robot models, rather than selling the data. Additionally, the company intends to share relevant research findings with the cities where it operates to help address
roboticsartificial-intelligenceautonomous-deliveryphysical-AIrobot-navigationreinforcement-learninglast-mile-deliverySoftBank bulks up its robotics portfolio with ABB Group’s robotics unit
Japanese conglomerate SoftBank Group is expanding its robotics portfolio by acquiring ABB Group’s robotics business unit based in Zurich for $5.375 billion. The deal, expected to close by mid-to-late 2026 pending regulatory approval, involves ABB’s robotics division which employs around 7,000 people and generated $2.3 billion in revenue in 2024, accounting for 7% of ABB’s total revenue. ABB’s robotics unit offers a range of robots for tasks such as picking, cleaning, and painting. Following the acquisition, Sami Atiya, the division head, will leave the company. SoftBank aims to revitalize the robotics spinoff, whose revenue declined from $2.5 billion in 2023 to $2.3 billion in 2024. SoftBank has been steadily increasing its investments in robotics, including stakes in established companies like AutoStore and startups such as Skild AI and Agile Robots, alongside launching its own SoftBank Robotics Group in 2014
roboticsSoftBankABB-Groupartificial-intelligencephysical-AIrobotics-acquisitionautomationRobots cut 30% travel time using human-like memory in smart factories
Researchers at South Korea’s Daegu Gyeongbuk Institute of Science and Technology (DGIST) have developed a new “Physical AI” technology that enhances the navigation efficiency of autonomous mobile robots (AMRs) in environments such as logistics centers and smart factories. This technology mimics human-like memory by modeling the social phenomenon of spreading and forgetting information, enabling robots to distinguish between relevant, real-time obstacles and outdated, unnecessary data. By forgetting obsolete information—such as obstacles that have been cleared—the robots avoid unnecessary detours, improving movement efficiency and productivity in complex, dynamic settings. Testing in a simulated logistics center demonstrated significant performance improvements, with average travel times reduced by up to 30.1% and task throughput increased by 18.0% compared to conventional ROS 2 navigation systems. The technology requires only 2D LiDAR sensors, making it cost-effective and easy to integrate as a plugin into existing ROS 2 navigation stacks without hardware modifications. Beyond industrial applications, this approach holds promise
robotsautonomous-mobile-robotsphysical-AIsmart-factorieslogistics-automationrobot-navigationcollective-intelligence-algorithmNVIDIA unveils brain-and-body stack to train next-gen humanoids
NVIDIA has introduced a comprehensive robotics stack aimed at advancing humanoid robot development by integrating physics simulation, AI reasoning, and infrastructure within its Isaac Lab platform. Central to this update are the open-source, GPU-accelerated Newton Physics Engine and the Isaac GR00T N1.6 robot foundation model. Newton, co-developed with Google DeepMind and Disney Research and managed by the Linux Foundation, enables highly realistic simulations of complex physical interactions—such as walking on uneven terrain or handling fragile objects—facilitating safer and more reliable transfer of robot skills from simulation to real-world environments. Early adopters include leading academic and industry robotics groups. Isaac GR00T N1.6 incorporates NVIDIA’s Cosmos Reason, a vision-language reasoning model designed for physical AI, which enhances humanoid robots’ ability to interpret ambiguous instructions, leverage prior knowledge, and generalize across tasks. This model supports simultaneous movement and object manipulation, tackling advanced challenges like opening heavy doors. Developers can fine-tune GR00T
roboticshumanoid-robotsNVIDIA-IsaacNewton-Physics-EngineAI-infrastructurerobot-simulationphysical-AIAWS, NVIDIA, and MassRobotics pick Diligent for first Physical AI Fellowship cohort - The Robot Report
MassRobotics, AWS, and NVIDIA have launched the Physical AI Fellowship to support startups integrating robotics and artificial intelligence for practical applications. Diligent Robotics, known for its AI-native mobile manipulator robot Moxi, was selected for the inaugural cohort. Moxi assists nurses in over 25 U.S. hospitals by performing routine tasks like medication and lab sample delivery, saving nearly 600,000 staff hours and completing over 1 million tasks. The fellowship offers Diligent Robotics $200,000 in AWS cloud credits, access to NVIDIA platforms and Deep Learning Institute resources, and support from MassRobotics’ testbed and ecosystem, aiming to accelerate development of autonomous humanoid robots and enhance Moxi’s intelligence layer. The Physical AI Fellowship is designed to fast-track startups building intelligent physical systems by providing technical guidance, hardware, and global networking opportunities. The program will culminate in showcases at major events including AWS re:Invent 2025. Diligent Robotics plans to use the fellowship to expand
roboticsartificial-intelligenceautomationhealthcare-robotsphysical-AIAWSNVIDIAInside Singapore's physical AI revolution
The article summarizes Episode 210 of The Robot Report Podcast, which centers on Singapore’s emerging leadership in physical AI and robotics. Key guests from the Singapore Economic Development Board (EDB), Certis Group, and the Home Team Science & Technology Agency discuss Singapore’s strategic initiatives to grow its robotics sector. The country leverages its strong manufacturing base, government incentives, and a collaborative ecosystem involving industry and academia to foster innovation and talent development. Emphasis is placed on the importance of integration, reliability, and scalability for successful deployment of robotics and AI technologies. The episode also covers notable robotics news, including Boston Dynamics’ Spot robot performing a public triple backflip, showcasing advancements in reinforcement learning for robot agility and recovery. Despite the impressive feat, Spot’s performance in America’s Got Talent did not advance to the quarterfinals. Additionally, Intuitive Surgical announced a permanent layoff of 331 employees (about 2% of its workforce) at its Sunnyvale headquarters. Lastly, John Deere expanded its agricultural
roboticsartificial-intelligencephysical-AISingaporeBoston-Dynamicsreinforcement-learningautomationHow does NVIDIA's Jetson Thor compare with other robot brains on the market? - The Robot Report
NVIDIA recently introduced the Jetson AGX Thor, a powerful AI and robotics developer kit designed to deliver supercomputer-level artificial intelligence performance within a compact, energy-efficient module consuming up to 130 watts. The Jetson Thor provides up to 2,070 FP4 teraflops of AI compute, enabling robots and machines to perform advanced “physical AI” tasks such as perception, decision-making, and control in real time directly on the device, without dependence on cloud computing. This capability addresses a major challenge in robotics by supporting multi-AI workflows that facilitate intelligent, real-time interactions between robots, humans, and the physical environment. The Jetson Thor is powered by the comprehensive NVIDIA Jetson software platform, which supports popular AI frameworks and generative AI models, ensuring compatibility across NVIDIA’s broader software ecosystem—from cloud to edge. This includes tools like NVIDIA Isaac for robotics simulation and development, NVIDIA Metropolis for vision AI, and Holoscan for real-time processing. The module’s high-performance
robotAINVIDIA-Jetsonrobotics-hardwareedge-computingphysical-AIAI-inferenceUjjwal Kumar steps down as president of Teradyne Robotics - The Robot Report
Ujjwal Kumar has stepped down as president of Teradyne Robotics Group, announcing his departure on LinkedIn while committing to remain with the company through September 2025 to assist in the transition to his successor, Jean-Pierre Hathout. During his tenure of over two years, Kumar helped expand the product and customer portfolios of Universal Robots (UR) and Mobile Industrial Robots (MiR), promoted Physical AI, and supported customer transformation efforts. Kumar did not disclose his next career move but expressed continued interest in business transformation, Physical AI, Industry 5.0, and automation. Teradyne Robotics, which includes UR (a leader in collaborative robot arms) and MiR (an autonomous mobile robot developer), has faced challenges recently, including a 17% year-over-year revenue decline in Q2 2025 and a workforce reduction of about 10% earlier in the year to better align with market conditions. Leadership changes at both UR and MiR aim to sharpen strategic focus and improve execution.
roboticscollaborative-robotsautonomous-mobile-robotsTeradyne-Roboticsindustry-5.0automationphysical-AIXpanner releases X1 autonomy retrofit kit to bring physical AI to construction - The Robot Report
Xpanner has launched its flagship X1 Kit, a physical AI-based retrofit system designed to enhance construction machinery by transforming existing equipment into “software-defined machinery” (SDM). The X1 Kit addresses key industry challenges such as labor shortages, safety risks, and inefficiencies by automating complex tasks across various brands and models without requiring new machinery purchases. The system has demonstrated significant improvements, including an 80% reduction in labor needs and a 50% decrease in operation time for pile driving in solar installations. Xpanner emphasizes that the X1 Kit continuously learns and adapts on the jobsite, creating a foundational AI infrastructure to boost productivity and reduce costs by over 50%. The X1 Kit integrates three core Xpanner technologies: Mango for precise machine control, M2 for environmental data processing and real-time command transmission, and a proprietary software platform that manages integration and user interaction with continuous remote updates. This task-specific automation approach focuses on individual construction tasks to collectively streamline entire workflows. Founded
robotconstruction-automationphysical-AIretrofit-kitsoftware-defined-machinerypile-drivingindustrial-roboticsPhysical AI takes center stage at RoboBusiness
RoboBusiness, held October 15-16 in Santa Clara, California, will debut the Physical AI Forum, focusing on the emerging field of physical AI in robotics. The forum will cover critical topics such as safety, simulation-to-reality reinforcement training, data curation, and deploying AI-powered robots. As the premier event for commercial robotics developers and suppliers, RoboBusiness features over 60 speakers, a startup workshop, the Pitchfire competition, and a surgical robotics track, alongside more than 100 exhibitors showcasing the latest robotics technologies. Key presentations at the Physical AI Forum include NVIDIA’s VP Deepu Talla discussing the transformative impact of generative AI on robotics, emphasizing simulation-first development and real-time edge deployment to enable adaptable, intelligent autonomy in unstructured environments. Dexterity’s founding engineer Robert Sun will present on their Physical AI platform that integrates multimodal AI with industrial robots to enhance warehouse automation through real-time adaptation and safety. ABB’s Thomas-Tianwei Wang will highlight AI integration across ABB’s
robotphysical-AIroboticsAI-powered-robotswarehouse-robotssimulation-to-realityedge-AIDigiKey, onsemi discuss the intersection of robotics and physical AI - The Robot Report
DigiKey and onsemi recently explored how advancements in sensing technologies and physical AI are driving the evolution of autonomous mobile robots (AMRs), which have the potential to transform industrial and commercial sectors. AMRs utilize a variety of sensors—including lidar, cameras, ultrasonic detectors, and radar—to enhance safety, improve productivity, and navigate complex environments. Similar to self-driving vehicles, AMRs employ technologies such as simultaneous localization and mapping (SLAM) to create real-time maps and localize themselves, enabling them to operate beyond controlled indoor settings into more unpredictable outdoor environments. These developments are supported by improvements in sensor integration, edge computing, and AI, which collectively make AMRs more autonomous, adaptive, and capable of performing a wider range of tasks safely alongside humans. The discussion also highlighted the shift in communication protocols within AMRs, moving from traditional CAN (Controller Area Network) to the newer 10BASE-T1S Ethernet-based protocol, led by onsemi. This protocol offers higher data rates (10 Mbps
roboticsautonomous-mobile-robotsphysical-AIsensorsindustrial-robotsedge-computingAI-integrationShengShu Technology launches Vidar multi-view physical AI training model - The Robot Report
ShengShu Technology, a Beijing-based company founded in March 2023 specializing in multimodal large language models, has launched Vidar, a multi-view physical AI training model designed to accelerate robot development. Vidar, which stands for “video diffusion for action reasoning,” leverages a combination of limited physical training data and generative video simulations to train embodied AI models. Unlike traditional methods that rely heavily on costly, hardware-dependent physical data collection or purely simulated environments lacking real-world variability, Vidar creates lifelike multi-view virtual training environments. This approach allows for scalable, robust training of AI agents capable of real-world tasks, reducing the need for extensive physical data by up to 1/80 to 1/1,200 compared to industry-leading models. Built on ShengShu’s flagship video-generation platform Vidu, Vidar employs a modular two-stage learning architecture that separates perceptual understanding from motor control. In the first stage, large-scale general and embodied video data train the perceptual
robotembodied-AIAI-training-modelsimulationgenerative-videorobotics-developmentphysical-AIFORT Robotics adds $18.9M to Series B funding for robotic safety - The Robot Report
FORT Robotics, a Philadelphia-based company specializing in remote control technology and safety for autonomous systems, has secured an additional $18.9 million in its Series B funding round led by Tiger Global. This brings the company’s total funding to $60.5 million. Founded in 2018, FORT Robotics provides a Robotics Control Platform designed to ensure safe, secure, and dynamic control of autonomous machines, supporting over 500 customers with approximately 12,000 units deployed across industries such as warehousing, agriculture, and construction. The company emphasizes enhancing human-machine collaboration while minimizing risks to people, assets, and data. The new capital will be used to enhance existing products by expanding communication protocols, API integrations, and international compliance, as well as to develop next-generation safety solutions featuring advanced data analytics tailored to the unique challenges of physical AI. FORT Robotics aims to accelerate the growth and implementation of its protective technologies as autonomous systems become more prevalent globally. The funding round attracted both returning investors—including Tiger Global,
roboticsautonomous-systemsrobotic-safetyphysical-AIhuman-machine-collaborationindustrial-automationrobotics-fundingLearn at RoboBusiness how Sim2Real is training robots for the real world - The Robot Report
The article highlights the upcoming RoboBusiness 2025 event in Silicon Valley, which will focus on advances in physical AI—combining simulation, reinforcement learning, and real-world data—to enhance robot deployment and reliability in dynamic environments such as e-commerce and logistics. A key feature will be a session showcasing Ambi Robotics’ AmbiStack logistics robot, which uses the PRIME-1 foundation model trained extensively in simulation to master complex tasks like 3D item stacking, akin to playing Tetris. This simulation-driven training, coupled with physical feedback, enables the robot to make real-time decisions and handle diverse packages efficiently. The session will be co-hosted by noted experts Prof. Ken Goldberg of UC Berkeley and Jeff Mahler, CTO and co-founder of Ambi Robotics. They will discuss scalable AI training approaches that improve robotic manipulation capabilities. RoboBusiness 2025 will also introduce the Physical AI Forum track, covering topics such as multi-model decision agents, AI-enhanced robot performance, and smarter data curation
roboticsartificial-intelligencesimulation-trainingwarehouse-automationphysical-AIrobotic-manipulationlogistics-robotsSkild AI is giving robots a brain - The Robot Report
Skild AI has introduced its vision for a generalized "Skild Brain," a versatile AI system designed to control a wide range of robots across different environments and tasks. This development represents a significant step in Physical AI, which integrates artificial intelligence with physical robotic systems capable of sensing, acting, and learning in real-world settings. Skild AI’s approach addresses Moravec’s paradox by enabling robots not only to perform traditionally "easy" tasks (like dancing or kung-fu) but also to tackle complex, everyday challenges such as climbing stairs under difficult conditions or assembling intricate items, tasks that require advanced vision and reasoning about physical interactions. Since closing a $300 million Series A funding round just over a year ago, Skild AI has expanded its team to over 25 employees and raised a total of $435 million. Physical AI is gaining momentum across the robotics industry, with other companies like Physical Intelligence pursuing similar goals of creating a universal robotic brain. This topic will be a major focus at RoboBusiness 202
robotroboticsartificial-intelligencephysical-AIrobot-controlmachine-learningautomationNVIDIA VP Deepu Talla to discuss physical AI at RoboBusiness - The Robot Report
At RoboBusiness 2025, Deepu Talla, NVIDIA’s vice president of robotics and edge AI, will deliver the opening keynote titled “Physical AI for the New Era of Robotics.” Scheduled for October 15 in Santa Clara, California, Talla will discuss how physical AI—where models perceive, reason, and act in real-world environments—is transforming robotics from static, rule-based automation to adaptable, intelligent autonomy capable of managing complex, unstructured tasks. NVIDIA is accelerating this shift through simulation-first development, foundation models, and real-time edge deployment, training robots in virtual environments before scaling them into physical applications. This advancement marks a significant milestone in integrating intelligent machines into the $50 trillion global economy. NVIDIA has positioned itself as a leader in physical AI with recent innovations such as Isaac GR00T N1.5, an updated customizable foundation model for humanoid robot reasoning, and Isaac GR00T-Dreams, a synthetic motion data generation blueprint. The NVIDIA Isaac platform is widely adopted
roboticsphysical-AINVIDIA-Isaachumanoid-robotsedge-AIautonomous-machinesrobotics-developmentRoboBusiness announces 2025 agenda
RoboBusiness 2025, scheduled for October 15-16 at the Santa Clara Convention Center, has unveiled its comprehensive conference agenda. Established in 2004, RoboBusiness is a leading event for commercial robotics developers and suppliers, produced by WTWH Media. The event will feature over 60 speakers, a startup workshop, a robotics startup competition, networking receptions, and more than 100 exhibitors showcasing cutting-edge robotics technologies and solutions. The conference will include six tracks, with new additions in physical AI and humanoids, an expanded field robotics track, and sessions on business development, enabling technologies, and design best practices. Notable companies participating include ABB, Amazon Robotics, NVIDIA, and Intuitive Surgical. Keynote presentations will highlight significant industry trends and innovations. NVIDIA’s Deepu Talla will open with a talk on “Physical AI,” emphasizing the integration of generative AI into robotics to enable adaptable, intelligent autonomy beyond traditional automation. Another session will focus on early commercial deployments of humanoid robots
roboticsAIhumanoid-robotsphysical-AIrobotics-conferenceedge-AIautomationGFT Technologies and NEURA Robotics partner to build software for physical AI - The Robot Report
NEURA Robotics has partnered with GFT Technologies SE to develop a software platform aimed at advancing physical AI, which integrates robotics with artificial intelligence. GFT, a global digital transformation company with expertise in AI, data, and high-performance architecture, is entering the robotics sector through this collaboration. The partnership leverages GFT’s experience in AI software and complex regulated industries to bridge the gap between AI insights and physical robotic actions, supporting the development of smarter, autonomous machines. NEURA Robotics, based in Metzingen, Germany, specializes in cognitive robotics that enable machines to learn, adapt, and operate autonomously in real-world environments. The company has developed collaborative robot arms and mobile manipulators and recently launched new robots alongside its Neuraverse ecosystem. This collaboration with GFT aligns with NEURA’s vision to bring cognitive robotics into practical applications, exemplified by its recent partnership with HD Hyundai on shipbuilding robots. Together, they aim to pioneer a new era of intelligent machines powered by advanced software and AI capabilities
roboticsartificial-intelligencephysical-AIcognitive-roboticssoftware-platformautonomous-machinesindustrial-robotsGenesis AI brings in $105M to build universal robotics foundation model - The Robot Report
Genesis AI, a physical AI research lab and robotics company, has emerged from stealth with $105 million in funding to develop a universal robotics foundation model (RFM) and a horizontal robotics platform. The company aims to advance "physical AI"—the intelligence enabling machines to perceive, understand, and interact with the real world—by leveraging digital AI foundations to create general-purpose robots with human-level intelligence. Founded by robotics Ph.D. Zhou Xian and former Mistral AI researcher Théophile Gervet, Genesis AI focuses on building a scalable data engine that unifies high-fidelity physics simulation, multimodal generative modeling, and large-scale real robot data collection to train robust, flexible, and cost-efficient robots. Physical labor accounts for an estimated $30 to $40 trillion of global GDP, yet over 95% remains unautomated due to limitations in current robotic systems, which are often narrow, brittle, and costly. Genesis AI seeks to overcome these challenges by generating rich synthetic data through
roboticsartificial-intelligencephysical-AIrobotics-foundation-modelautomationrobotics-platformAI-simulationNVIDIA releases cloud-to-robot computing platforms for physical AI, humanoid development - The Robot Report
robothumanoidAINVIDIAroboticsautomationphysical-AIRoboBusiness 2025 call for speakers now open
robotroboticshumanoid-robotsphysical-AIfield-roboticsenabling-technologiesRoboBusiness