Task allocation for multi-robot teams in dynamic environments

Abstract

Multi-robot task allocation is a well known and widely researched decision-making problem that is difficult to solve in reasonable time even for small instances. Additional complexity is added by the fact that the parameters of the system may change over time, which happens either by external stimuli or by the task execution itself. One of the common causes behind these changes is the movement of executors or tasks. This paper tackles a problem of multi-task, multi-robot allocation in a such an environment. Formulated and solved is a specific decision-making problem. Performed is an experimental comparison of a dedicated solution algorithm with known methods for the more general Multidimensional Knapsack and Covering problem. Empirical evaluation illustrates that a dedicated approach is competitive and often necessary, as the general approach proves to be too slow.