Toward Mass Customization of a Robot’s Morphology Design for Improving Area Coverage

Abstract

Floor cleaning robots have been developed to cater to building maintenance needs. Complete area coverage is crucial for a floor cleaning robot, and its morphology design plays a vital role in realizing complete area coverage. However, floor cleaning robots with fixed morphologies have difficulty in achieving a high area coverage performance. Mass customization of a robot’s morphology would improve its productivity in terms of area coverage. This paper proposes a novel system that can be used for mass customizing the morphology of a robot to improve area coverage performance in an environment of interest. The customized morphology is determined through an optimization technique by considering an environment of interest and design constraints. The area coverage of a candidate morphology design is evaluated by simulating the robot navigation in an environment of interest. Generalized pattern search, particle swarm optimization, and surrogate optimization are independently considered optimization techniques. Experiments have been conducted considering the cases of robot deployments. The statistical conclusions on experimental results validate that the proposed system can synthesize a morphology that significantly improves the area coverage performance in an environment of interest.