Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields
The coverage path planning (CPP) algorithms play a key role in autonomous robot applications, making area coverage operations efficient and cost-effective. The extension of coverage path planning algorithms to multi-robot operation is still widely unveiled despite the cyclical nature of agricultural...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10272336/ |
| _version_ | 1797660884108050432 |
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| author | Murugaraj Govindaraju Daniele Fontanelli S. Selva Kumar Anju S. Pillai |
| author_facet | Murugaraj Govindaraju Daniele Fontanelli S. Selva Kumar Anju S. Pillai |
| author_sort | Murugaraj Govindaraju |
| collection | DOAJ |
| description | The coverage path planning (CPP) algorithms play a key role in autonomous robot applications, making area coverage operations efficient and cost-effective. The extension of coverage path planning algorithms to multi-robot operation is still widely unveiled despite the cyclical nature of agricultural operations, i.e., comprising repeated actions. The problem of coverage path planning for multi-robot operations is addressed in this paper. The three possible forms of multi-robot coverage algorithms evolved from the basic single-robot coverage algorithm based on the elementary trapezoidal method or zig-zag movements. Furthermore, an optimized coverage path planning algorithm for multiple in-row robots meant to control the weeding in an agricultural field is proposed. The parameters of the agricultural field are supposed to be known upfront, opening the application of an offline planning algorithm. The proposed algorithm stands tall in terms of distance covered with no repeated coverage compared with other possible solutions, nearing the results of single robot coverage (for which the planning is trivially simpler and there is no coverage repetition). Online adjustments in the multi-robot area coverage are also considered, and the proposed algorithm proves to be effective in simulation in this respect as well. The quantitative evaluation proves that, in the proposed algorithm with a team size of 15(<inline-formula> <tex-math notation="LaTeX">$\mathrm {n=15}$ </tex-math></inline-formula>), the average distance consumed by each robot to cover the field taken for the study is only 65% of that of the other two algorithms. Also shows increase in the team size (n) leads to a decrease in consumption. This algorithm provides a solution for the autonomous operation of multi-robots to cover the fields with static obstacles at a regular pattern which is a common demand of many agricultural processes. |
| first_indexed | 2024-03-11T18:36:20Z |
| format | Article |
| id | doaj.art-e70fa69c8d694ace9ca1026994e8077b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T18:36:20Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e70fa69c8d694ace9ca1026994e8077b2023-10-12T23:00:52ZengIEEEIEEE Access2169-35362023-01-011110986810988410.1109/ACCESS.2023.332223010272336Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy FieldsMurugaraj Govindaraju0https://orcid.org/0000-0002-0086-017XDaniele Fontanelli1https://orcid.org/0000-0002-5486-9989S. Selva Kumar2https://orcid.org/0000-0002-2510-5306Anju S. Pillai3https://orcid.org/0000-0001-5298-6789Department of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, IndiaDepartment of Industrial Engineering, University of Trento, Trento, ItalyDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, IndiaDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, IndiaThe coverage path planning (CPP) algorithms play a key role in autonomous robot applications, making area coverage operations efficient and cost-effective. The extension of coverage path planning algorithms to multi-robot operation is still widely unveiled despite the cyclical nature of agricultural operations, i.e., comprising repeated actions. The problem of coverage path planning for multi-robot operations is addressed in this paper. The three possible forms of multi-robot coverage algorithms evolved from the basic single-robot coverage algorithm based on the elementary trapezoidal method or zig-zag movements. Furthermore, an optimized coverage path planning algorithm for multiple in-row robots meant to control the weeding in an agricultural field is proposed. The parameters of the agricultural field are supposed to be known upfront, opening the application of an offline planning algorithm. The proposed algorithm stands tall in terms of distance covered with no repeated coverage compared with other possible solutions, nearing the results of single robot coverage (for which the planning is trivially simpler and there is no coverage repetition). Online adjustments in the multi-robot area coverage are also considered, and the proposed algorithm proves to be effective in simulation in this respect as well. The quantitative evaluation proves that, in the proposed algorithm with a team size of 15(<inline-formula> <tex-math notation="LaTeX">$\mathrm {n=15}$ </tex-math></inline-formula>), the average distance consumed by each robot to cover the field taken for the study is only 65% of that of the other two algorithms. Also shows increase in the team size (n) leads to a decrease in consumption. This algorithm provides a solution for the autonomous operation of multi-robots to cover the fields with static obstacles at a regular pattern which is a common demand of many agricultural processes.https://ieeexplore.ieee.org/document/10272336/Coverage path planningmulti-robot path planningagricultural robotsweeding robotsautonomous robots |
| spellingShingle | Murugaraj Govindaraju Daniele Fontanelli S. Selva Kumar Anju S. Pillai Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields IEEE Access Coverage path planning multi-robot path planning agricultural robots weeding robots autonomous robots |
| title | Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields |
| title_full | Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields |
| title_fullStr | Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields |
| title_full_unstemmed | Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields |
| title_short | Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields |
| title_sort | optimized offline coverage path planning algorithm for multi robot for weeding in paddy fields |
| topic | Coverage path planning multi-robot path planning agricultural robots weeding robots autonomous robots |
| url | https://ieeexplore.ieee.org/document/10272336/ |
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