The software developed focuses on robotic manipulation, assembly, and precision control, utilizing ROS2 for enhanced functionality. Key features include mobile manipulation and robot assistance, enabling autonomous operation. The platform supports hyper-realistic simulations for testing and validation, facilitating rapid prototyping and deployment. Custom solutions and reusable modules are offered to streamline robotics development, ensuring efficient integration into existing systems.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
Faraday Future's AI subsidiary, FFAI, announced its accelerated expansion into commercial robotics at Automate 2026 in Chicago. The company showcased its 'one brain, multiple forms' robotics platform and revealed that June robot shipments are expected to exceed 100 units, bringing total first-half deliveries to over 220 units, surpassing its initial target ahead of schedule. This milestone is significant as it marks FFAI's transition from an education-focused robotics business to industrial automation, targeting commercial deployments across manufacturing, logistics, and research. The company presented a range of robotics products, including the All-New Futurist humanoid robot and the FF Faber mobile manipulator series, highlighting its commitment to integrating advanced AI technologies into various applications. Looking ahead, FFAI outlined a broader strategy focused on an open embodied AI ecosystem, which includes its EAI Brain software platform and an EAI Data Factory for operational data collection. No further timeline was disclosed at the time of publication.
Artificial Intelligence Events News ai All-New Futurist Automate 2026At the WAIC 2026 exhibition, Aoyi Technology showcased its full range of ROHand dexterous hands, having served over 200 clients in the embodied intelligence sector. The company introduced the OpenArm dual-arm robot to address the need for vast amounts of real data, enhancing the capabilities of its dexterous hands through a combination of hardware and data collection. This development is significant as it not only improves the dexterous hand's ability to perform tasks but also allows companies to gather specialized training data at a lower cost. The ROHand can mimic human hand movements with an accuracy of 0.6 seconds and lift weights up to 30 kg, demonstrating its versatility across various applications from industrial assembly to consumer services. Looking ahead, Aoyi's integration of the OpenArm robot with the ROHand is expected to enhance the dexterous hand's adaptability across different scenarios. The combination of hardware and data solutions positions Aoyi to address the industry's data scarcity, paving the way for broader applications in real-world environments. No further timeline was disclosed at the time of publication.
Dexterous Robots Data Collection Embodied Intelligence Robotics SolutionsGuident CEO Harald Braun on the RMCC architecture, IRLS risk identification system, and why California’s 2026 AV mandates validate six years of platform development.
Recent trends in the robotics industry indicate a shift from mere mobility to operational intelligence, particularly in humanoid robots. Companies are now focusing on practical applications such as tool handling and assembly, highlighting the importance of force sensing technology. As robots engage in physical tasks, understanding the force exerted becomes crucial for effective operation. This transition underscores the growing significance of six-dimensional force sensors, which are evolving from optional components in industrial robots to essential infrastructure for next-generation intelligent robots. The recent funding rounds exceeding 100 million yuan reflect a broader interest from both traditional investors and state-owned enterprises, signaling a pivotal moment in the industry's development. Looking ahead, the demand for comprehensive sensing, control, and manufacturing infrastructure will likely increase as the humanoid robotics sector matures. The complexity of enabling robots to perform sustained tasks, such as assembly and material handling, will challenge developers to innovate beyond flashy capabilities and focus on the intricate details that drive commercialization.
Humanoid Robots Force Sensing Technology Industrial Automation Robotics InnovationThe development of robotics begins long before physical assembly, relying heavily on simulations to validate designs and refine algorithms. These simulations demand significant computational resources, making system benchmarking crucial to identify hardware limitations early in the process. By measuring workstation performance under demanding workloads, engineers can establish a performance baseline that aids in spotting potential bottlenecks. Understanding how different hardware components affect simulation performance is essential for robotics development. Whether using macOS, Windows, or Linux, benchmarking helps determine if slowdowns are due to software changes or hardware limitations. Key components such as the processor, graphics card, memory, and storage play varying roles in performance, and the weakest link can dictate the overall experience. As robotics projects grow in complexity, the need for robust hardware becomes increasingly important. Engineers should focus on comprehensive benchmarking to ensure their systems can handle the demands of their simulations. No further timeline was disclosed at the time of publication.
Components Robot simulation ABB RobotStudio automation cpu delmiaGravity has introduced a unified embodied intelligence framework designed for long-range and complex robotic tasks. This framework, built on a Mixture-of-Transformers (MoT) architecture, integrates visual language models (VLM) for instruction and scene understanding, task reasoning, and world modeling to predict future states and evaluate sub-goals. It also incorporates tactile and force feedback, prior knowledge, and multi-modal supervision to enhance task execution and adaptability. The significance of Gravity's framework lies in its ability to improve the success rate of complex operations that require precise contact and autonomous error correction. By combining AR Transformer and Diffusion Transformer, Gravity enables robots to simulate multiple strategies and assess risks before executing tasks. This advancement shifts robotic capabilities from reactive responses to proactive planning, making it suitable for applications in precision assembly, complex sorting, and flexible manufacturing. Looking ahead, Gravity aims to further develop its complete system, having already implemented components like Gravity VLA and Gravity 4D WAM. The focus will be on enhancing the framework's ability to learn from real-world experiences, thereby creating a continuous feedback loop that improves operational efficiency and adaptability in various industrial contexts. No further timeline was disclosed at the time of publication.
Robotic Frameworks Embodied Intelligence Task Automation Machine Learning RoboticsGS Caltex announced the completion of a 200 billion won ($135 million) turnaround at its Yeosu refinery, utilizing robots, artificial intelligence, and digital tools to enhance safety and operational efficiency. This large-scale maintenance operation involved halting production for intensive inspections and replacing aged components, laying the groundwork for safer and more efficient plant operations. The significance of this turnaround lies in GS Caltex's integration of digital and AI solutions, which are part of the company's broader digital transformation strategy. By digitalizing core operational systems, the refinery aims to improve workplace practices and boost overall competitiveness. The deployment of technologies like MOVision and tube-cleaning robots addresses specific operational challenges, such as locating electric motor-operated valves and enhancing thermal efficiency. Looking ahead, GS Caltex plans to continue innovating within the manufacturing sector by leveraging its DAX strategies. The company's commitment to integrating on-site expertise with advanced technologies is expected to further enhance efficiency and safety in future operations. No further timeline was disclosed at the time of publication.
All NewsKAIST's mechanical engineering team, led by Professor Park Hai-won, announced a breakthrough in robotic technology on July 16. They developed a four-legged robot capable of autonomously selecting and switching between various gaits in real-time, enabling it to navigate complex outdoor environments with speed and stability. This innovation is significant as it integrates a new control architecture called APT-RL (Action Pre-training Reinforcement Learning based on Transformers), which allows the robot to learn movement through computer simulations rather than traditional motion capture. The robot, named KAIST HOUND, demonstrated its capabilities by traversing diverse terrains, achieving peak speeds of 6 meters per second, faster than an average cyclist. Future developments to watch include the potential applications of this technology in disaster response, defense tasks, and industrial inspections. The research was published in the July issue of the journal Science Robotics, highlighting its importance in advancing the field of robotic control and physical AI.
Four-Legged Robots Robotics Technology AI Autonomous Navigation1X has introduced the NEO robot hand, showcasing its ability to perform intricate tasks with remarkable precision. The hand features 25 degrees of freedom and utilizes a tendon-driven structure, mimicking human muscle and tendon systems, allowing for smooth and natural movements. The NEO hand can perform tasks such as separating grapes, twisting light bulbs, and pulling zippers, demonstrating capabilities that closely resemble human dexterity. The significance of the NEO robot hand lies in its potential applications as a household assistant, capable of performing chores, caring for the elderly, and aiding in rehabilitation. Its design incorporates numerous sensors that enable it to not only grasp objects but also assess how to grip them without causing damage. This advancement marks a critical step towards creating robots that can seamlessly integrate into daily life. Looking ahead, the NEO hand's uncanny resemblance to human hands raises questions about the 'uncanny valley' effect, where human-like robots elicit discomfort. As 1X aims to position the NEO as a versatile home assistant, the balance between functionality and human likeness will be crucial in its acceptance. No further timeline was disclosed at the time of publication.
Robotics Dexterous Manipulation AI Technology Human-Robot InteractionGeneral Intuition, a New York-based company, has proposed a groundbreaking approach to training robots using millions of hours of gaming footage instead of vast amounts of real-world data. In June 2026, the company completed a $320 million Series A funding round, achieving a valuation of $2.3 billion, led by renowned investor Vinod Khosla. The significance of General Intuition's method lies in its potential to revolutionize how robots learn spatial reasoning and physical intuition. By utilizing gaming data, the company claims to have pre-trained a spatial reasoning model that allows quadruped robots to navigate unfamiliar environments with minimal real-world data, challenging traditional training methods that rely heavily on real-world scenarios. Looking ahead, the success of General Intuition will depend on its ability to validate its technology in diverse real-world environments beyond office settings. The company's vision of creating a 'robot brain' for universal physical AI could redefine the operational frameworks for future robotics, potentially surpassing existing systems like Windows and Android in impact.
AI Robotics Gaming Technology Machine LearningTombot, a robotics company based in Los Angeles, has announced the completion of a $7 million Series A3 funding round led by Caduceus Capital Partners and Wavemaker 360. This brings the company's total funding to over $13 million, with more than 23,000 preorders for Jennie, an AI-driven robotic Labrador puppy, already secured before product delivery. The significance of Jennie lies in its potential to address the growing issue of loneliness among seniors, particularly those suffering from dementia and mild cognitive impairment. With over 300 million individuals globally affected by these conditions, Tombot aims to provide a medical-grade emotional support device that requires no feeding, walking, or maintenance, thus offering a viable companionship option for the elderly. Looking ahead, Tombot's focus will be on continuous updates to Jennie's behavior and voice commands through an accompanying mobile app. The response from investors and the market indicates a serious consideration of robotic companions as a solution to the pressing challenges of aging populations and caregiver shortages. No further timeline was disclosed at the time of publication.
Emotional Support Robots Elderly Care Technology AI Companions RoboticsA comprehensive industry analysis of Physical AI — covering Embodied AI, Field AI, Factory AI, VLM, World Model, VLA, and the VLA vs WAM architecture debate. Includes 20+ companies, 28 references, and the RobotToday Physical AI Landscape diagram. July 2026.
OLO Robotics brings ROS 2, Gazebo, Nav2 and MoveIt 2 into one browser-based platform. Discover how its appliance, Cloud Sim, and live data handling accelerate robot development.
Ukraine’s ‘Sub Sea Baby’ autonomous torpedo struck a Russian Kilo-class submarine inside Novorossiysk harbour in December 2025 — the first confirmed underwater drone attack on a submarine in history. The U.S. Navy is requesting $5.3 billion for unmanned maritime systems in FY2026, a 70 percent year-on-year increase. Saronic Technologies went from prototype to $392 million production contract in under 12 months. And DARPA’s Manta Ray XL-UUV completed full-scale sea trials. This article maps the maritime autonomous systems revolution — from Ukraine’s improvised Black Sea fleet to the Pentagon’s hybrid manned–unmanned force of the 2030s, and from Saronic’s Franklin, Louisiana shipyard to Boeing’s 85-tonne robot submarine.
From clinical diagnostics to self-driving labs: a deep analysis of laboratory robotics technologies, mass-production maturity timelines across 12 vertical sectors, 26 key companies, and the investment landscape shaping lab automation through 2030.
Saronic Technologies closes a $1.75B Series D led by Kleiner Perkins at a $9.25B valuation to scale autonomous surface vessel production and revitalize U.S. naval shipbuilding capacity.
Exclusive interview with DFRobot Founder & CEO Ricky Ye on lowering barriers in AI and robotics, the evolution of HUSKYLENS, open-source hardware, and the future of embodied AI.
Spirit AI partners with JD.com to deploy embodied AI robots in retail, combining VLA models, real-world data loops, and scalable automation.
How the cost equation of modern warfare has inverted: a $500 AI-guided drone now rivals a $2 million precision missile in tactical effect. Part One of the Future Warfare Series examines the unit economics, supply chain realities, and venture capital forces reshaping defence procurement — from Ukraine's 1.7 million FPV drones to Anduril's $30 billion factory-as-weapon bet.
The SUNNY-T2000 signals a shift in heavy cargo UAVs, showing how two-ton unmanned aircraft are reshaping regional and industrial air logistics.
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