首页|New Robotics Study Findings Reported from Xi’an Jiaotong University (Collision-f ree Motion Generation Based On Stochastic Optimization and Composite Signed Dist ance Field Networks of Articulated Robot)
New Robotics Study Findings Reported from Xi’an Jiaotong University (Collision-f ree Motion Generation Based On Stochastic Optimization and Composite Signed Dist ance Field Networks of Articulated Robot)
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 – Investigators publish new report on Ro botics. According to news originating from Xi’an,People’s Republic of China, by NewsRx correspondents, research stated, “Safe robot motion generation iscritic al for practical applications from manufacturing to homes. In this work, we prop osed a stochasticoptimization-basedmotion generation method to generate collisi on-free and time-optimal motion for thearticulated robot represented by composi te signed distance field (SDF) networks.”
Xi’anPeople’s Republic of ChinaAsiaEmerging TechnologiesGaussian ProcessesMachine LearningRobotRoboticsStochastic OptimizationXi’an Jiaotong University
NETL
NSTL
