首页|New Findings on Robotics from Harbin Institute of Technology Summarized (Evolvin g Robotic Hand Morphology Through Grasping and Learning)
New Findings on Robotics from Harbin Institute of Technology Summarized (Evolvin g Robotic Hand Morphology Through Grasping and Learning)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news originating from Harbin, People's Republic of China, by Ne wsRx correspondents, research stated, "Creatures can co-evolve their biological structures and behaviors under environmental pressures. Leveraging biomimetic ev olution algorithms (referred to as co-design or co-optimization), a diverse rang e of robots with environmental adaptation has been generated." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from the Harbin Institut e of Technology, "However, implementing these evolutionary methods or results in real-world robots, especially in the case of robotic hands, was not easy. In th is context, this work presents a comprehensive self-optimization scheme for robo tic hands that encompasses both software and hardware components. This scheme en ables robots to autonomously refine their morphology through the integration of hardware gradients and reinforcement learning within parallel environments, ther eby enhancing their adaptability to a variety of grasping tasks. For the hardwar e aspect, we developed a reconfigurable hand prototype with 37 variable hardware parameters (i.e., joint stiffness, the length of phalanges, finger location, an d palm curvature) adjusted by mechanical components. Leveraging the adjustable h ardware and 20 motors, this hand achieves full actuation and can dynamically adj ust its morphology. The training results indicate that the fitness score of the self-optimizing hand exceeds that of original designs in this instance. The hard ware parameters can be further fine-tuned in response to task variations."
HarbinPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsRobotsHarbin Institute of Technology
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