Simultaneous task assignment and path planning using mixed-integer linear programming and potential field method

This paper investigates a task assignment and path planning problem in a situation where threats exist. Common task assignment algorithms obtain straight line paths during the task assignment phase and then plan the paths considering the threats, which can decrease performance of task assignment and task success rate. Therefore, task assignment with real-time path planning is presented in this paper using Mixed-Integer Linear Programming(MILP) and potential field method. Real-time path planning usually requires amount of computational time but MILP simplifies the task assignment problem so real-time path planning can be applied to task assignment. Task selection algorithm is also presented to compensate the modified sub-optimal MILP. MILP task selection algorithm is compared with a brute-force search algorithm which obtains optimal solutions in situations without threats. Simulation results are presented to show the advantages of MILP task selection algorithm in avoiding threats and performing tasks successfully.