An Optimized Multirobot Task Allocation

Abstract

Multirobot systems (MRS) hold the promise of improved performance and increased fault tolerance for large-scale problems. One of the most important aspects in the design of MRS is the allocation of tasks among the robots in a productive and efficient manner. Optimal solutions to multirobot task allocation (MRTA) can be found through an exhaustive search. Since there are ways in which m tasks can be assigned to n robots, an exhaustive search is often not possible. Task allocation methodologies must ensure that not only the global mission is achieved, but also the tasks are well distributed among the robots. This paper presents task allocation methodologies for MRS by considering their capability in terms of time and space. A two-phase solution methodology is used to solve the MRTA problem wherein the task capacity of the robots is determined during the first phase and the task allocation optimization is done during the second phase using linear programming (LP).