首页|Southeast University Reports Findings in Robotics (Deep Reinforcement Learning Framework-based Flow Rate Rejection Control of Soft Magnetic Miniature Robots)
Southeast University Reports Findings in Robotics (Deep Reinforcement Learning Framework-based Flow Rate Rejection Control of Soft Magnetic Miniature Robots)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Robotics. According to news reporting from Nanjing, People’s Republic of China, by NewsRx journalists, research stated, “Soft magnetic miniature robots (SMMRs) have potential biomedical applications due to their flexible size and mobility to access confined environments. However, navigating the robot to a goal site with precise control performance and high repeatability in unstructured environments, especially in flow rate conditions, still remains a challenge.”
NanjingPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotReinforcement LearningRobotRoboticsSoutheast University
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