首页|Sun Yat-sen University Reports Findings in Robotics (A reinforcement learning en hanced pseudo-inverse approach to self-collision avoidance of redundant robots)
Sun Yat-sen University Reports Findings in Robotics (A reinforcement learning en hanced pseudo-inverse approach to self-collision avoidance of redundant robots)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Robotics is the subjec t of a report. According to news reportingoriginating from Guangzhou, People’s Republic of China, by NewsRx correspondents, research stated,“Redundant robots offer greater flexibility compared to non-redundant ones but are susceptible to increasedcollision risks when the end-effector approaches the robot’s own links . Redundant degrees of freedom(DoFs) present an opportunity for collision avoid ance; however, selecting an appropriate inverse kinematics(IK) solution remains challenging due to the infinite possible solutions.”
GuangzhouPeople’s Republic of ChinaA siaEmerging TechnologiesMachine LearningNano-robotReinforcement LearningRisk and PreventionRobotics
NETL
NSTL
