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Task allocation has been a well studied problem. In most prior problemformulations, it is assumed that each task is associated with a unique set ofresource requirements. In the scope of multi-robot task allocation problem,these requirements can be satisfied by a coalition of robots. In this paper, weintroduce a more general formulation of multi-robot task allocation problemthat allows more than one option for specifying the set of taskrequirements--satisfying any one of the options will satisfy the task. Wereferred to this new problem as the multi-robot task allocation problem withtask variants. First, we theoretically show that this extension fortunatelydoes not impact the complexity class, which is still NP-complete. For solutionmethods, we adapt two previous greedy methods for the task allocation problemwithout task variants to solve this new problem and analyze theireffectiveness. In particular, we "flatten" the new problem to the problemwithout task variants, modify the previous methods to solve the flattenedproblem, and prove that the bounds still hold. Finally, we thoroughly evaluatethese two methods along with a random baseline to demonstrate their efficacyfor the new problem.

Allocation of Multi-Robot Tasks with Task Variants