Research On Multi-robot Task Allocation Based On Similar MTSP And GA With Elite Set Strategy

The Multi-robot Task Allocation(MRTA)is based on the Multi-robot Systems(MRS),which assigns the tasks to each robot in a certain optimization condition.Now the single robot is unable to meet the requirements of complex tasks,the research and application of multi-robot is particularly urgent.Firstly,this paper establishes a task allocation model of the Similar Multiple Traveling Salesman Problem(SMTSP).An improved Genetic Algorithm(GA)with the elite set strategy is proposed to optimize the allocation under different optimization objectives by changing a tunable weight parameter.Compared with the traditional algorithm,the improved algorithm gets faster convergence and retains the diversity of the population by swapping,sliding and flipping evolutionary operation of the elite set.Secondly,this paper analyses the results of task allocation with restrictions between some task points.The algorithm is proved to be effective in solving the practical problems,such as signal interruption and the collapse of the logistics transportation;Finally,the simulation experiments show that the genetic algorithm with elite set strategy in this paper gets faster convergence,and the approximate optimal solution with balanced path and less energy consumption is obtained by optimizing the total distance length and the maximum completion time with a balanced weight parameter.The MRTA optimization method proposed in this paper has wide utilization prospects,such as logistics and distribution,space scheduling,battlefield distribution.