Towards Robotic Swarm Inspection: Simulation to Real

Abstract

Robotic swarm inspection for structures offers a flexible, scalable, and cost-effective solution in comparison to human inspection such as the benefit of being resilient to individual failures, larger general coverage, and flexibility in sensing. One novel destination for such applications is space. Given the demand in human spaceflight through new efforts such as NASA’s Artemis I and SpaceX’s Starship the need to monitor physical spacecraft conditions becomes a priority. These robot swarms could be deployed in on-orbit satellite hulls, human space capsules, or future inhabited space structures. With routine monitoring in the harsh space environment, this solution offers a safe alternative against the risk in human inspections. This work moves towards this reality in three major points. First, this work presents a physics based simulation of a Bayesian inspection algorithm for randomized grid surfaces through a swarm of small-scale wheeled robots. Second, an optimization framework based off particle swarm optimization that is deployable on Amazon Web Services’ multi-node clusters. We use this framework to find a set of heuristic parameters that show improvements in our defined criteria. Third, we introduce novel hardware development that enables collision avoidance for physical deployment and experiments. With this, the work sets up the pathway to bring optimized algorithm parameters into a close relationship with hardware experiments.