Complexity (Jan 2021)
Toward Pleomorphic Reconfigurable Robots for Optimum Coverage
Abstract
Buildings are constructed for accommodating living and industrial needs. Floor cleaning robots have been developed to cater to the demand of these buildings. Area coverage and coverage time are crucial performance factors of a floor cleaning robot. Reconfigurable tiling robots have been introduced over fixed shape robots to improve area coverage in floor cleaning applications compared to robots with fixed morphologies. However, area coverage and coverage time of a tiling robot compromised one another. This study proposes a novel concept that considers the ability of a tiling robot to configure both its morphology and size according to the environment. This concept is inspired by the pleomorphism that could be seen in bacteria. In this regard, P-hTetro, a pleomorphic tiling robot that can reconfigure its morphology and size, is considered. A novel coverage strategy for realizing the size reconfiguration is also proposed. According to this strategy, the robot covers obstacle-free areas with its maximum size, while an obstacle cluster is covered after shrinking to an optimum size. The optimum size for reconfiguration is determined by the genetic algorithm based on the arrangement of the environment. The performance and behavior of the proposed P-hTetro have been compared against that of an existing tiling robot which has a fixed size. According to the statistical outcomes, a tiling robot with the ability to reconfigure its size can significantly improve the performance in the aspects of area coverage and coverage time compared to a tiling robot with no ability to reconfigure its size.