OPTIMAL COVERAGE PATH PLANNING FOR TRACTORS IN HILLY AREAS BASED ON ENERGY CONSUMPTION MODEL, 20-31.

Tao Liu, Junmin Li, Simon X. Yang, Zhidong Gong, Zhi li Liu, Hao Zhong, and Qiang Fu

References

  1. [1] I.A. Hameed, A. La Cour-Harbo, and O.L. Osen, Side-to-side3D coverage path planning approach for agricultural robotsto minimize skip/overlap areas between swaths, Robotics andAutonomous Systems, 76, 2016, 36–45.
  2. [2] E. Glorieux, P. Franciosa, and D. Ceglarek, Coverage pathplanning with targetted viewpoint sampling for robotic free-form surface inspection, Robotics and Computer-IntegratedManufacturing, 61, 2020.
  3. [3] X. Miao, J. Lee, and B.Y. Kang, Scalable Coverage path plan-ning for cleaning robots using rectangular map decompositionon large environments, IEEE Access, 6, 2018, 38200–38215.
  4. [4] M.A.V.J. Muthugala, A.V. Le, and E.S. Cruz, A self-organizingfuzzy logic classifier for benchmarking robot-aided blasting ofship hulls, Sensors, 20(11), 2020.
  5. [5] D.C. Slaughter, D.K. Giles, and D. Downey, Autonomousrobotic weed control systems: A review, Computers andElectronics in Agriculture, 61(1), 2008, 63–78.
  6. [6] S. Fountas, N. Mylonas, and I. Malounas, Agricultural roboticsfor field operations, Sensors, 20(9), 2020, 27.
  7. [7] S. Aggarwal and N. Kumar, Path planning techniques forunmanned aerial vehicles: A review, solutions, and challenges,Computer Communications, 149, 2020, 270–299.
  8. [8] H.L. Wang, C.J. Zhang, and Y. Song, Robot Arm PerceptiveExploration based Significant Slam in Search and Rescue En-vironment, International Journal of Robotics and Automation,33(4), 2018, 394–406.
  9. [9] A. Majeed and S. Lee, A new coverage flight path planningalgorithm based on footprint sweep fitting for unmanned aerialvehicle navigation in urban environments, Applied Sciences-Basel, 9(7), 2019.
  10. [10] E. Menendez, J.G. Victores, and R. Montero, Tunnel structuralinspection and assessment using an autonomous robotic system,Automation in Construction, 87, 2018, 117–126.
  11. [11] A. Bakdi, A. Hentout, and H. Boutami, Optimal path plan-ning and execution for mobile robots using genetic algorithmand adaptive fuzzy-logic control, Robotics and AutonomousSystems, 89, 2017, 95–109.
  12. [12] B.H. Qiang, Z.L. Liu, and Y.F. Wang, Service compositionbased on improved genetic algorithm and analytical hierarchyprocess, International Journal of Robotics and Automation,33(2), 2018, 169–178.
  13. [13] L. Wang and C. Luo, A hybrid genetic Tabu search algorithmfor mobile robot to solve AS/RS path planning, InternationalJournal of Robotics and Automation, 33(2), 2018, 161–168.
  14. [14] F.H. Ajeil, I.K. Ibraheem, and M.A. Sahib, Multi-objectivepath planning of an autonomous mobile robot using hybridPSO-MFB optimization algorithm, Applied Soft Computing,89, 2020.
  15. [15] M. Brand, M. Masuda, and N. Wehner, Ant Colony Optimiza-tion algorithm for robot path planning, International Con-ference on Computer Design and Applications (Qinhuangdao,China, 2010).
  16. [16] X.M. You, S. Liu, and C. Zhang, An improved ant colonysystem algorithm for robot path planning and performanceanalysis, International Journal of Robotics and Automation,33(5), 2018, 527–533.
  17. [17] J.X. Jiang and J.B. Xin, Path planning of a mobile robot in afree-space environment using Q-learning, Progress in ArtificialIntelligence, 8(1), 2019, 133–142.
  18. [18] B. Hao and Z.P. Yan, Recovery path planning for an agriculturalmobile robot by Dubins-RRT algorithm, International Journalof Robotics and Automation, 33(2), 2018, 202–207.
  19. [19] S. Dogru and L. Marques, A-Based solution to the coveragepath planning problem (Springer, Cham, 2017).
  20. [20] F.Y. Xie and X.P. Shi, A global path planning algorithm formanned submersible based on improved ant colony algorithms,International Journal of Robotics and Automation, 36(4), 2021,204–210.
  21. [21] W. Zhang, S.L. Wei, and J. Zeng, Multi-UUV path planningbased on improved artificial potential field method, Inter-national Journal of Robotics and Automation, 36(4), 2021,231–239.
  22. [22] U. Orozco-Rosas, O. Montiel, and R. Sepulveda, Mobile robotpath planning using membrane evolutionary artificial potentialfield, Applied Soft Computing, 77, 2019, 236–251.
  23. [23] D.M. Zhao, W. Xiong, and Z.Y. Shu, Simulated annealing witha hybrid local search for solving the traveling salesman problem,Journal of Computational and Theoretical Nanoscience, 12(7),2015, 1165–1169.
  24. [24] B.K. Ayawli, X. Mei, M.Q. Shen, Optimized RRT-A pathplanning method for mobile robots in partially known envi-ronment, Information Technology and Control, 48(2), 2019,179–194.
  25. [25] M. Shen, S. Wang, and S. Wang, Simulation study on coveragepath planning of autonomous tasks in hilly farmland basedon energy consumption model, Mathematical Problems inEngineering, 2020, 2020, 1–15.
  26. [26] J. Li, Z. Xu, and D. Zhu, Bio-inspired intelligence withapplications to robotics: A survey (2021).
  27. [27] S. Markaki, C. Panagiotakis, and D. Lasthiotaki, Image sortingvia a reduction in travelling salesman problem, IET ImageProcessing, 14(1), 2020, 31–39.
  28. [28] A.E.-S. Ezugwu, A.O. Adewumi, and M.E. Frincu, Simulatedannealing based symbiotic organisms search optimization al-gorithm for traveling salesman problem, Expert Systems withApplications, 77, 2017, 189–210.
  29. [29] Z. Zhang, Z. Xu, and S. Luan, Opposition-based ant colonyoptimization algorithm for the traveling salesman problem,Mathematics, 8(10), 2020.
  30. [30] S.-h. Zhan, J. Lin, and Z.-j. Zhang, List-based simulated an-nealing algorithm for traveling salesman problem, Computa-tional Intelligence and Neuroscience, 2016, 2016.
  31. [31] L. Kov´acs, A. Ag´ardi, and T. B´anyai, Fitness landscape anal-ysis and edge weighting-based optimization of vehicle routingproblems, Processes, 8(11), 2020, 1363.
  32. [32] W. Gao, Modified ant colony optimization with improved tourconstruction and pheromone updating strategies for travelingsalesman problem, Soft Computing, 2020.
  33. [33] Y. Harrath, Three-step metaheuristic for the multiple ob-jective multiple traveling salesmen problem, InternationalJournal of Applied Metaheuristic Computing, 11(4), 2020,130–148.
  34. [34] J. Jin and L. Tang, Optimal coverage path planning for arablefarming on 2d surfaces, Transactions of the Asabe, 53(1), 2010,283–295.1131

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