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.

Automated Generation of Site Map Graphs for Robot-Inclusive Tactile Marker Placement

“…The typical way of resolving operational problems often involve improving the robot's equipment and programs to enable the robot to explore and detect its surroundings better. Examples of such improvements include deployments of advanced control methods [35], complex hardware enhancements [36], reconfigurable mechanisms [37], and algorithmic improvements [38], [39]. The robot eventually becomes more complex and costly to surpass environmental challenges during operation.…”

Design of Robot-Inclusive Vertical Green Landscape

“…This approach brings together roboticians and architects to integrate the behaviour derived from the structure of spaces with that of the robot. Based on challenges posed by the human environment, roboticians typically seek to overcome the current limitations of the robot by improving on its functionality such as robot perception [31], reconfigurable design [32], human-robot interaction [33], control [34], and energy efficiency [35]. Instead of increasing the complexity of the robot design based on customised solutions for the robot, those challenges could be easily addressed following a top-down approach that changes the spatial environment in which the robot operates in instead, to better fit the environment to the robot's tasks instead of solely upgrading the robot without considering its working area.…”

A Review on Human–Robot Proxemics

“…The autonomy of service robots ranges from partially to fully autonomous, which can perform a meaningful and purposive task based on information gathered from their environment, user, and knowledge [2]. These service robots play a vital role in the present world since the service robots are utilized in enormous application areas including education [3][4][5], health-care [6,7], entertainment [8,9], cleaning [10][11][12], and guidance [13][14][15]. Moreover, the utilization of service robots to support day-to-day tasks improves the quality of life.…”