Title：Robot motion planning method and system based on graph Wasserstein self-encoding network
Country：China
Patent No.：202110571993.8
Legal Status：Authorized
Inventor：Chongkun Xia, Bin Liang,Xueqian Wang, Houde Liu, Songping Mai
Assignee：International Graduate School at Shenzhen, Tsinghua University
Address：Tsinghua Campus, Xili University Town, Nanshan District, Shenzhen City 518062, Guangdong Province
Filing Date：2021-05-25
Issue Date：2021-08-20
Abstract：
The invention discloses a robot motion planning method and system based on a graph Wasserstein self-encoding network. The method comprises the following steps of S1, constructing the graph Wasserstein self-encoding network (GraphWAE); S2, conducting non-uniform sampling distribution representation learning based on the GraphWAE; and S3, conducting robot motion planning based on the GraphWAE. Compared with the prior art, the robot motion planning method and system have the beneficial effects that the non-obstacle area in the robot configuration space is represented and learned through the GraphWAE, and serves as a sample generator of a mainstream sampling planning algorithm, the planning exploration process is guided to be carried out in the non-obstacle area, the planning time is shortened, and the planning path quality and the success rate are improved.
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