TY - GEN
T1 - Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot
AU - Kalimuthu, Manivannan
AU - Hayat, Abdullah Aamir
AU - Pathmakumar, Thejus
AU - Veerajagadheswar, Prabakaran
AU - Mohan, Rajesh Elara
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/7/5
Y1 - 2023/7/5
N2 - The use of reconfigurable robots for cleaning is ideal due to their versatility and ability to adapt to the environment. However, frequent shape changes consume a lot of energy, limiting the battery life. This paper presents a framework that uses metaheuristic algorithms to determine the optimal shape of the robot to maximize coverage and minimize energy consumption. The approach uses Speed constrained multi-objective particle swarm optimization (SMPSO) and Strength Pareto Evolutionary Algorithm2 (SPEA2) to generate the optimal shapes out of high number of possible morphologies for a given area and its map layout. The unique feature of this approach is the implementation of footprint-based path planning that can be used for all robot configurations. The effectiveness of the framework is demonstrated using a Tetris-inspired robot named Smorphi. The results show that the proposed framework is suitable for selecting optimal energy-efficient morphology of the Tetris inspired reconfigurable robot for area coverage task.
AB - The use of reconfigurable robots for cleaning is ideal due to their versatility and ability to adapt to the environment. However, frequent shape changes consume a lot of energy, limiting the battery life. This paper presents a framework that uses metaheuristic algorithms to determine the optimal shape of the robot to maximize coverage and minimize energy consumption. The approach uses Speed constrained multi-objective particle swarm optimization (SMPSO) and Strength Pareto Evolutionary Algorithm2 (SPEA2) to generate the optimal shapes out of high number of possible morphologies for a given area and its map layout. The unique feature of this approach is the implementation of footprint-based path planning that can be used for all robot configurations. The effectiveness of the framework is demonstrated using a Tetris-inspired robot named Smorphi. The results show that the proposed framework is suitable for selecting optimal energy-efficient morphology of the Tetris inspired reconfigurable robot for area coverage task.
KW - Area coverage
KW - Design principles
KW - Footprint based path planning
KW - Reconfigurable robot
KW - Smorphi
UR - http://www.scopus.com/inward/record.url?scp=85179886248&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179886248&partnerID=8YFLogxK
U2 - 10.1145/3610419.3610464
DO - 10.1145/3610419.3610464
M3 - Conference contribution
AN - SCOPUS:85179886248
T3 - ACM International Conference Proceeding Series
BT - Proceedings of 2023 6th International Conference on Advances in Robotics, AIR 2023
PB - Association for Computing Machinery
T2 - 6th International Conference on Advances in Robotics, AIR 2023
Y2 - 5 July 2023 through 8 July 2023
ER -
