Abstract
In recent years, a rising trend of floor cleaning robots could be observed in the consumer electronic market. Area coverage performance is a crucial factor that determines the overall productivity of a floor cleaning robot. Nevertheless, the area coverage performance of commercially available floor cleaning robots is limited due to narrow spaces resulting from complex furniture arrangements. Traditionally, new robot designs (both hardware and algorithmic) are explored to over-come the coverage limitations. Developments of reconfiguration mechanisms and path planning algorithms for floor cleaning robots could be considered as examples. This paper proposes a novel concept called "design by robot," enabling a floor cleaning robot to make suggestions on workspace modifications to maximize its area coverage performance in a given workspace. In this regard, the robot analyzes a workspace to be cleaned through internal simulations based on the metric map of the workspace. A metaheuristic optimization technique determines the optimum placings of objects. Particle Swarm Optimization (PSO), Surrogate Optimization (SO), and Generalized Pattern Search (GPS) are individually used in this regard. Experiments, including scenarios of robot deployments, have been considered for validation. The statistical outcomes of the experimental results validate that the area coverage performance of a floor cleaning robot could be significantly improved by considering the workspace modifications suggested by the robot. Moreover, the proposed concept "design by robot" enables users to gain significantly improved performance from floor cleaning robots through collaboration.