Simultaneous Task Allocation, Data Routing, and Transmission Scheduling in Mobile Multi-Robot Teams

In the context of coordination of mobile multi-robot/agent networked teams, we present an integrated model that simultaneously addresses two problems arising in multi-robot missions: (i) task allocation and task scheduling; and (ii) communication provisioning in the multi-hop mobile ad hoc network built by the team. The integrated model is based on a mixed integer linear programming (MILP) formulation, which is solved in a centralized mode. For the communication part, the model solution outputs data routing policies and data transmission schedules that are aimed to maximize data delivery throughput to/from control centers. The trade-off between task and network performance optimization is strategically controlled. A refinement procedure is defined that allows to further improve communications by also minimizing network delays. We report a computational analysis of the integrated MILP model and an evaluation of the impact of a number of parameters on the trade-off between computational load and quality of the output. Results show that the model is computationally affordable for reasonably sized scenarios, and can effectively balance different performance trade-offs.