TakkTile
TakkTile developed a low-cost tactile sensor technology for robotic hands and grippers, using barometric pressure sensors embedded in soft rubber. Originally a Harvard research spinout targeting affordable robotics sensing.
RobotToday Initiative
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
Yimu Technology Showcases Physical AI's Capabilities at WAIC 2026
At WAIC 2026, Yimu Technology attracted significant attention with its demonstration involving two identical peanuts. The exhibit illustrated the concept that while visual cues may be indistinguishable, tactile feedback reveals critical differences in texture and resilience. This highlights the importance of physical interaction in understanding the physical world. The significance of this demonstration lies in its implications for Physical AI. Traditional robots have struggled to interpret tactile information, often failing in tasks requiring sensitivity, such as handling fragile items. Yimu Technology emphasizes that the key to advancing robotics is not merely increasing model size but ensuring robots receive accurate physical feedback from their environment. Looking ahead, the focus will be on how effectively robots can integrate this tactile feedback into their operations. Yimu Technology's approach, which utilizes optical systems to measure minute deformations, could revolutionize how robots interact with their surroundings. No further timeline was disclosed at the time of publication.
Physical AI Tactile Sensors Robotics Machine Learning
mimic Robotics Launches Comprehensive Platform for Advanced Dexterous Robot Manipulation
mimic Robotics has unveiled a new robotic hand, the mimic hand M1, along with the mimic wearable U1 exoskeleton and a proprietary software platform. This integrated system aims to enhance general-purpose dexterous manipulation in industrial robots by addressing the challenge of collecting high-quality training data for AI models that perform human-like tasks. The significance of this launch lies in mimic Robotics' approach to design, which focuses on human hand morphology rather than traditional two-finger grippers. The mimic hand M1 features 15 actuated degrees of freedom and is capable of handling payloads over 25 kg, while the mimic wearable U1 allows human operators to demonstrate tasks in real-time, improving data collection for AI training. Looking ahead, the company’s innovative middleware and teleoperation software are expected to enhance robot control and AI inference speed. No further timeline was disclosed at the time of publication.
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RoboScience Unveils First Cloud-Based Large Model for Robotics at WAIC
At the WAIC, RoboScience showcased a groundbreaking cloud-based embodied large model named Visics, capable of controlling multiple robotic hands. This innovation allows for seamless switching between different robotic hands while maintaining operational efficiency, demonstrating the ability to recognize and grasp various objects autonomously within 30 seconds. The significance of this development lies in its potential to revolutionize robotic operations across diverse applications. By enabling a single model to adapt to various hand configurations, Visics enhances the versatility of robotic systems, allowing them to perform complex tasks without the need for extensive retraining when hardware changes occur. Looking ahead, the industry will be keen to observe how Visics performs in real-world scenarios and its ability to execute long-term tasks by integrating multiple actions. No further timeline was disclosed at the time of publication.
Robotics Cloud Computing AI Automation Object Recognition
Six Robots Assemble a 3.5-Meter Great Wall Model Using 81,920 Blocks at WAIC
At the World Artificial Intelligence Conference (WAIC), six robots from General Embodied Intelligence Company, Yuanli Lingji, undertook a challenging task to assemble a Great Wall model using 81,920 micro building blocks over 15 hours. Each robot was required to complete approximately 910 assembly actions per hour, achieving a speed comparable to skilled human workers. This demonstration highlights the complexities of robotic assembly, as traditional industrial robots operate under fixed conditions, while block assembly requires real-time perception and adaptability to varying positions and angles. The robots needed to maintain sub-millimeter precision throughout the task, pushing the limits of robotic capabilities and mimicking human dexterity. The execution team consisted of four desktop robots and two humanoid wheeled robots, each equipped with independent perception, decision-making, and execution abilities. The challenge tested multi-agent collaboration in a dynamic environment, emphasizing the need for real-time negotiation and coordination among robots to adapt to unforeseen circumstances during the assembly process. No further timeline was disclosed at the time of publication.
Robotic Assembly AI Technology Collaborative Robotics Precision Engineering
Dahuang Technology Showcases Advanced AI Multimodal Capabilities at WAIC 2026
On July 17, 2026, the World Artificial Intelligence Conference (WAIC) commenced in Shanghai, focusing on the theme 'Intelligent Partners, Co-Creating the Future.' Dahuang Technology presented its AI multimodal capabilities, showcasing a comprehensive system that includes understanding, connecting, interacting, and controlling complex data. The demonstration highlighted the company's transition from video-centric solutions to a broader AI multimodal framework. Dahuang Technology's Sports AI system, based on the BlackEye multimodal spatial model, was a key feature, providing real-time analysis of sports events. This system can automatically label players, track movements, and generate slow-motion replays, demonstrating the AI's ability to comprehend complex video scenarios. The technology has already been validated in high-profile events like the 2026 World Cup and the Paris Olympics. The company also introduced its AI multimodal perception compression technology, achieving over tenfold compression efficiency while maintaining video quality. This capability is crucial for applications in drone inspections, remote communications, and robotic operations, addressing the growing demands for bandwidth and data transmission efficiency in various sectors. No further timeline was disclosed at the time of publication.
AI Multimodal Technology Video AI Data Compression Sports AI Human-AI Interaction
Graduate Student Develops NASA Robot Assembly Algorithm for Satellite Antennas
Sarah Downs, a graduate student at Texas A&M University, has developed an algorithm for NASA that enables robots to assemble satellites in space. This algorithm addresses the classic peg-in-hole problem by allowing robots to insert antennas accurately into designated spots. Downs's work is significant as it enhances the capabilities of robots operating in the challenging environment of outer space. The importance of Downs's research lies in its potential to improve satellite assembly processes, which are critical for space missions. By creating a robot that can perform tasks without relying on vision systems, Downs addresses the challenges posed by the harsh conditions of space where cameras may fail. This innovation could lead to more reliable and efficient satellite deployment in future missions. Looking ahead, Downs plans to continue her research on satellite assembly and manipulation at a larger scale. As she progresses in her Ph.D. studies, her work will likely contribute to advancements in robotics that could transform how satellites are constructed and maintained in orbit. No further timeline was disclosed at the time of publication.
Type-ti Ieee-member-news Robots Nasa Student-member Satellites
1X Introduces Advanced 25-Degree-of-Freedom Hands for NEO Humanoid Robot
1X has launched a new tendon-driven robotic hand for its NEO humanoid platform, featuring 25 degrees of freedom. This design enhances dexterity, strength, and tactile sensing, enabling advanced AI-driven manipulation capabilities. The introduction of these hands aims to eliminate the 'hardware ceiling' that has previously restricted humanoid robots, allowing for more human-like manipulation. The hands can perform various tasks, including assembling LEGO models and using tools, showcasing their versatility and advanced functionality. Looking ahead, 1X has established a dedicated production line and plans to manufacture up to 10,000 units this year, which will facilitate broader deployment of the NEO humanoid platform. No further timeline was disclosed at the time of publication.
Humanoids News 1x artificial intelligence automation embodied ai
The Rise of Force Sensing Technology in China's Robotics Industry
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 Innovation
Innovative Robotic Hand Uses Single Motor for Versatile Gripping Solutions
A new robotic hand has been developed that can switch between multiple grippers using just one motor. This innovation addresses the need for robots to handle a wide variety of objects across different environments, including factories and households. The ability to manage diverse objects with a single motor reduces the complexity associated with traditional robotic hands, which typically rely on multiple motors and intricate control systems. This advancement not only lowers the weight and cost of robotic systems but also minimizes the risk of failures and simplifies control mechanisms. As the demand for adaptable robotic solutions grows, this new technology could significantly impact various sectors. Future developments may focus on enhancing the versatility and efficiency of robotic hands, although no further timeline was disclosed at the time of publication.
Robotics
Robbyant Launches Upgraded LingBot-VLA 2.0 AI Model for Advanced Robotics
Robbyant, a company specializing in embodied AI under Ant Group, has unveiled the upgraded LingBot-VLA 2.0 model. This next-generation vision-language-action model enhances morphological generalization, degrees of freedom support, and deployment efficiency, addressing a critical gap in the embodied AI industry. The significance of LingBot-VLA 2.0 lies in its extensive pre-training on 60,000 hours of real-world data, which includes interactions from 20 different robot morphologies. This upgrade allows for improved whole-body control and dual-arm manipulation, achieving leading scores on benchmarks, thus demonstrating its effectiveness in industrial-scale deployment. Looking ahead, the introduction of a version optimized for efficient post-training and a threefold increase in inference efficiency positions LingBot-VLA 2.0 as a strong contender for real-time commercial applications. No further timeline was disclosed at the time of publication.
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