Optimal Morphologies of n-Omino-Based Reconfigurable Robot for Area Coverage Task Using Metaheuristic Optimization

Reconfigurable robots design based on polyominos or n-Omino is increasingly being explored in cleaning and maintenance (CnM) tasks due to their ability change shape using intra- inter-reconfiguration, resulting various footprints of the robot. On one hand, reconfiguration during a CnM task given environment map results enhanced area coverage over fixed-form robots. However, it also consumes more energy additional effort required continuously while covering map, leading deterioration overall performance. This paper proposes new strategy for n-Omino-based select range optimal morphologies that maximizes minimizes consumption. The “morphology” two factors: footprint obtained by varying angles between blocks number blocks, i.e., “n”. proposed approach combines Footprint-Based Complete Path planner (FBCP) with metaheuristic optimization algorithm identify an reconfigurable robot’s configuration, assuming consumption proportional path length taken demonstrated robot named Smorphi, which has square-shaped omino holonomic locomotion from monomino tetromino. Three different simulated environments are used find Smorphi three techniques, namely, MOEA/D, OMOPSO, HypE. study show morphology produced this efficient, minimizing maximizing coverage. Furthermore, HypE identified as efficient generating took less time converge than other algorithms.