Reliable distribution of computational load in robot teams

Abstract Modern multi-robot systems often need to solve computationally intensive tasks but operate with limited compute resources and in the presence of failures. Cooperating share computational between robots at edge reduces execution time. We introduce evaluate a new computation load management technology for teams robots: Reliable Autonomous Mobile Programs (RAMPs). RAMPs use information about available team cost model decide where execute. are implemented ROS on collection Raspberry Pi-based robots. The performance is evaluated using route planning, typical computationally-intensive robotics application. A systematic study demonstrates high likelihood optimal or near-optimal distribution hence efficient resource utilisation. successfully complete simultaneous, successive, robot failures network failures, while preserving distribution.