Performance analysis of bid calculation methods in multirobot market-based task allocation

In this study, the empirical results of a market-based task allocation method for heterogeneous and homogeneous robot teams and different types of tasks in 2 different environments are presented. The proposed method allocates robots to tasks through a parallel multiitem auction-based process. The main contribution of the proposed method is energy-based bid calculations, which take into account both the heterogeneity of the robot team and features of the tasks. The multirobot task allocation problem is considered as the optimal assignment problem and the Hungarian algorithm is used to clear the auctions. Simulations are carried out using energy-based, distance-based, and time-based bid calculation methods. The methods are implemented using a 3-type task set: cleaning a space, carrying an object, and monitoring. The tasks may have different sensitivities and/or priority levels. Simulations show that robot-task allocations of all of the methods result in similar utility values when single-type and/or same-featured tasks are used. However, for different-type and/or different-featured tasks, the proposed energy-based bid calculation method assigns a greater number of high-sensitivity tasks compared to the other 2 methods while consuming almost the same amount of energy in both environments. Additionally, the energy-based method has a filtering behavior for high-priority tasks. These properties of the proposed method increase the efficiency of the robot team.