Cooperative Object Transport with Humanoid Robots using RRT Path Planning and Re-Planning

The multi-agent cooperation has been proved useful in executing many complex tasks. In our previous paper, we proposed a path planning algorithm based on a random sampling for the sake of the multi-agent cooperation. However, the action path of the robots is liable to be deviated by the noise in the real world. Thus, some correction mechanism is required to reduce the differences between the planned path and the real one. In this paper, we propose a re-planning method to solve the above-mentioned difficulty. The applicability of this method is confirmed with the experiment using two humanoid robots, in which they have re-generated path plans according to their locations detected by their own cameras