Core Viewpoint - Jinghua New Materials (603683) has developed flexible tactile sensor electronic skin for dexterous hands, enabling precise perception of object touch and contours [1] Group 1: Company Developments - The company has created a tactile perception technology that provides key sensing solutions for highly flexible dexterous hands and industrial robots [1] - Jinghua New Materials continues to deepen its focus on tactile perception technology for various applications [1]

Core Insights - The current advancements in Vision-Language-Action (VLA) models enhance robots' perception capabilities, but human understanding of the physical world extends beyond mere visual perception [1] - Touch perception captures dimensions that vision and language cannot cover, such as surface texture and material properties, which are crucial for physical intelligence [1] Company Highlights - Yimu Technology showcased its self-developed bionic visual-tactile sensor at the 2025 International Conference on Intelligent Robots and Systems (IROS) [1] - The sensor enables robotic arms to perform complex tasks, such as grasping fragile items, demonstrating its practical applications [1] - The sensor features a significantly reduced thickness while maintaining a bionic fingertip shape, allowing compatibility with various dexterous hands and robotic platforms [1] Technical Innovations - The sensor addresses challenges like light field baseline drift and spatial calculation blind spots through unique optical design [1] - The optimized ultra-soft elastomer material enhances wear resistance while maintaining high sensitivity [1] - An end-to-end AI algorithm processes multimodal tactile information, including 3D morphology, texture, and force fields [1] Market Outlook - The bionic visual-tactile sensor is set to be commercialized soon, indicating a shift towards more embodied intelligence in robotics [1]

Core Insights - The core viewpoint of the articles emphasizes the significance of tactile perception technology in the evolution of humanoid robots, enabling them to interact more effectively with their environment and expand their application scenarios [1][2]. Group 1: Company Overview - The company, HeShan Technology, has been focused on the exploration and development of tactile perception technology since its establishment in 2017, becoming a key supplier in the robotic dexterous hand and embodied intelligence industry chain [1]. - The CEO, Ma Yang, highlighted that the company has developed the world's first artificial intelligence tactile perception chip, which was launched in 2022 after over four years of research [2]. Group 2: Technological Advancements - Tactile perception is described as a critical component for robots to function as effective assistants, with the company achieving a tactile perception capability rated at approximately 70 out of 100 [2]. - The company has introduced a "simulation + real data" collaborative system to accelerate technology iteration, which allows for 90% of initial training to be completed without real-world scenarios, significantly reducing costs [6]. Group 3: Industry Trends - At the 2025 World Robot Conference, 80-90% of robotic hand manufacturers and over 80% of robot manufacturers showcased products empowered by the company's tactile perception technology [3]. - The industry is shifting focus from merely comparing degrees of freedom in robotic hands to emphasizing their practical capabilities in real-world tasks [4]. Group 4: Application Scenarios - The company is exploring interesting applications in the agricultural sector, such as the harvesting of agricultural products and the preprocessing of crayfish, with a prototype already developed [5][4]. - Robots are now capable of performing flexible tasks in industrial settings, such as the insertion and extraction of cable harnesses and the delicate handling of components [4].

Core Viewpoint - The article discusses the development of a tactile sensing-based shared control strategy for prosthetic hands, which enhances the precision of control for amputees while reducing fatigue, thereby improving the acceptance of myoelectric prosthetic hands [1][2]. Group 1: Tactile Sensing Technology - Tactile sensing technology enables prosthetic hands to detect contact, prevent slipping, and adjust grip strength, assisting users in daily tasks such as pouring water, drinking, and handling objects [1]. - The proposed shared control strategy incorporates multi-stage grasping and force level switching functions to help amputees perform multi-object sorting tasks more efficiently [2]. Group 2: Research Framework - The overall framework of the tactile sensing-based shared control strategy includes three main components: gesture recognition to decode user intent, activation of pre-shaping and stable grasping functions based on contact state detection, and determination of force level switching or multi-stage grasping based on gesture consistency [3]. - The autonomous control module is responsible for determining the activated functions and generating corresponding motor commands based on user intent and fingertip tactile sensing [3]. Group 3: User Study - A user study involved 8 able-bodied participants and 3 upper-limb amputees, focusing on three common daily activities: multi-object sorting, filling a cup with water, and squeezing toothpaste [4]. - Results indicated that the multi-stage grasping function significantly improved operational efficiency (shorter completion time), while the force level switching function enhanced operational quality (higher success rate), effectively reducing muscle usage and receiving positive feedback from users [4]. Group 4: Discussion and Future Directions - The study emphasizes the need for a comprehensive evaluation of new prosthetic hand functions, including task performance, control burden, and usability measurements [5]. - User-centered assessments are established as crucial for evaluating prosthetic systems, highlighting the importance of understanding user willingness to activate and accept new functions in the design of prosthetic hands [5].