Random sampling algorithm for multi-agent cooperation planning
Shotaro Kamio, Hitoshi Iba · 2005
The cooperation of several robots is needed for complex tasks. The cooperation methods for multiple robots generally require exact goal or sub-goal positions. However, it is difficult to direct the goal or sub-goal positions to multiple robots for the sake of cooperation with each other. Planning algorithms reduce the burden for this purpose. In this paper, we propose a multi-agent planning algorithm based on a random sampling method. This method doesn't require the exact sub-goal positions nor the times at which cooperation occurs. The effectiveness of this approach is empirically shown by simulation results.