Multi-robot charged system search-based optimal path planning in static environments

This paper proposes an optimal path planning approach based on Charged System Search (CSS) algorithms. The approach is applied to multiple mobile robots on holonomic wheeled platforms. Optimization problems (o.p.s) are defined for each robot to minimize the weighted sum of four objective functions whose minimization targets four path planning objectives. The CSS algorithms are mapped onto the o.p.s considering that the fitness functions are the objective functions, the search spare is the solution space, the agents (charged particles) are the mobile robots, and the population of agents is the set of mobile robots. Therefore, the optimal solutions to the o.p.s are the optimal paths. The new path planning approach is validated by experiments, and a comparison with other nature-inspired optimization-based path planning approaches is given.