Multiple Extrema Seeking by Swarm Robots Based on Distributed Optimization
Kazunori Sakurama, Hirosuke Yasuki, Sin-ichiro Nishida
This paper deals with a seeking problem for multiple extrema by swarm robots. Extreme seeking is a task to find an extremum on a field with gradients like temperature profiles. By using swarm robots, it is expected to find multiple extrema at once. In this paper, we design a controller to spread the robots on the multiple extrema, rather than to gather them on one extremum. Our proposed method controls the variance of the robots in order to appropriately spread them out. Especially, this controller is distributed, so each robot uses only its local information.