Cooperative receding horizon path planning of multiple robots by genetic algorithm

Integrating the feature of the mission and mission region of the multiple robots, our paper focuses not only on determining an efficient route (usually called path planning) for a group of moving robots, but on allocating a set of robots to a number of targets (usually called mission planning) as well. Taking the total rewards of the group of robots, the movement nonholonomic constraints of UGV, the survival probability of the threaten area and the collision avoidance between robots into account, we formulate a reasonable objective function and some practical constrains. To solve the optimal control problem, Cooperative Receding Horizon Control Stategy (CRH) and Genetic Algorithm are applied to obtain the optimal control law to maximize the objective function and meet all the needs of movement constraints, collision avoidance, etc. The steps how to get the CRH control law and the methods to choose the Chromosome Coding, Genetic Operator such as Selection Operator, Crossover Operation and Mutation Operator are given in detail in the paper The Numerical simulation illustrates the group of robots can automatically assign different targets and to visit this targets with reletively efficient routines to make sure to gain the maximum rewards during a given time period in the mission region, so the. validity of the proposed Genetic Algorithm based CRHpath planning method is proved.