A Path Planning Strategy of Wearable Manipulators with Target Pointing End Effectors

Electronics

Xinrui Wang¹  Kaifan Zou²  Xin’an Gao²  Meng Zhu²  Zhong Li²  Wei Tong²  Xiaorong Guan²  Huibin Li² 

[1] No.208 Research Institute of China Ordnance Industries, Beijing 102202, China;School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;

关键词: manipulator;    path planning;    RRT;    DMPs;    target pointing end effector;   

DOI  :  10.3390/electronics11101615

来源: DOAJ

【 摘 要 】

End effectors like firearms, cameras and fire water guns can be classified as pointing end effectors. When installed on wearable manipulators, a new function can be given to the wearer. Different from gripper end effectors (GEEs), target pointing end effectors (TPEEs) have different working tasks, and the requirements for path planning are also different. There is very limited research on wearable manipulators with TPEEs. Meanwhile, manipulator with GEE path planning tends to be mature, but with a relatively low efficiency concerning its algorithm in solving high-dimensional problems. In this paper, a degree of freedom (DOF) allocation scheme and a path planning strategy (unlike manipulator with gripper end effector) were proposed for manipulators with a target pointing end effector in order to reduce the difficulty of path planning. Besides, this paper describes a new algorithm-dimension rapid-exploration random tree (dimension-RRT) to divide the manipulator DOFs into groups and unify DOFs groups by adding a fake time. The dimension-RRT was compared with the rapid-exploration random tree star algorithm (RRT*) in the same simulation environment; when there are 500 random points, the dimension-RRT time consumption is 0.556 of RRT* and the path length is 0.5 of RRT *. To quickly obtain a path that can avoid the human body, dynamic movement primitives (DMPs) were used to simulate typical spatial motion path and obstacle avoidance path efficiently.

【 授权许可】

Unknown