Trajectory equilibrium state detection and avoidance algorithm for multi-autonomous potential field mobile robots

Abstract

An exceptionally efficient algorithm for local multi-mobile robot autonomous navigation is presented. The algorithm guides each robot independently although the algorithmic principle is identical for each robot. This approach is a combination of a novel rule-based mathematical algorithm and the virtual force field (VFF) navigational method. The need for the combinational algorithm is due to VFF's inability to guide efficiently multi-autonomous robots in the same environment owing to a trajectory equilibrium state (TES). TES is a new state that dramatically degrades performance of the VFF and is firstly identified and defined within this study. Test results of the novel algorithm yield near-optimum trajectories for the mobile robots.