Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot

Manivannan Kalimuthu; Abdullah Aamir Hayat; Thejus Pathmakumar; Prabakaran Veerajagadheswar; Rajesh Elara Mohan

doi:10.1145/3610419.3610464

Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot

Manivannan Kalimuthu
, Abdullah Aamir Hayat
, Thejus Pathmakumar
, Prabakaran Veerajagadheswar
, Rajesh Elara Mohan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of 2023 6th International Conference on Advances in Robotics, AIR 2023
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450399807
DOIs	https://doi.org/10.1145/3610419.3610464
Publication status	Published - Jul 5 2023
Externally published	Yes
Event	6th International Conference on Advances in Robotics, AIR 2023 - Ropar, India Duration: Jul 5 2023 → Jul 8 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	6th International Conference on Advances in Robotics, AIR 2023
Country/Territory	India
City	Ropar
Period	7/5/23 → 7/8/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Area coverage
Design principles
Footprint based path planning
Reconfigurable robot
Smorphi

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3610419.3610464

Cite this

Kalimuthu, M., Hayat, A. A., Pathmakumar, T., Veerajagadheswar, P., & Mohan, R. E. (2023). Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot. In Proceedings of 2023 6th International Conference on Advances in Robotics, AIR 2023 Article 45 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3610419.3610464

Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot. / Kalimuthu, Manivannan; Hayat, Abdullah Aamir; Pathmakumar, Thejus et al.
Proceedings of 2023 6th International Conference on Advances in Robotics, AIR 2023. Association for Computing Machinery, 2023. 45 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kalimuthu, M, Hayat, AA, Pathmakumar, T, Veerajagadheswar, P & Mohan, RE 2023, Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot. in Proceedings of 2023 6th International Conference on Advances in Robotics, AIR 2023., 45, ACM International Conference Proceeding Series, Association for Computing Machinery, 6th International Conference on Advances in Robotics, AIR 2023, Ropar, India, 7/5/23. https://doi.org/10.1145/3610419.3610464

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abstract = "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.",

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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.

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Efficient Area Coverage with Optimal Morphologies of Reconfigurable Smorphi Robot

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this