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Robot navigation path planning in power plant based on improved wolf pack algorithm

Published: 22 November 2021 Publication History

Abstract

Substation is an important part of power system, and regular inspection is very important to ensure the safe operation of substation. Patrol robot can patrol power equipment in few or unattended substations. In order to obtain the global optimal path of the robot, this paper proposes a navigation path planning based on improved wolf pack algorithm (IWPA). Firstly, the path optimization in discrete domain is studied by introducing position-order coding in initialization stage. Secondly, improve the moving step of the attack behavior and improve the efficiency of the running behavior. Finally, the updating rules of IWPA increase the diversity of wolves to enhance the global optimization ability of the algorithm. Finally, both IWPA and Wolf Pack Algorithm (WPA) are simulated, and the results show that the improved algorithm is more effective in solving the navigation path planning problem of inspection robot.

References

[1]
Bkp A, Gbl B, Ap C, A review: On path planning strategies for navigation of mobile robot. Defence Technology, vol. 15, no. 4, pp. 582-606, 2019.
[2]
Jiang Mio, Qiao Hongyu and Shi Zhigang. Based on an improved glowworm swarm algorithm path planning problem research. Journal of Changchun University of Technology (Natural Science Edition), vol. 039, no. 006, pp. 562-567, 2018.
[3]
LI Kui.AGV Path Planning Based on Chaos Particle Swarm Optimization Algorithm.Packaging Engineering, vol. 39, no. 23, pp. 32-37, 2018.
[4]
Ouyang H, Quan Y, Gao L, Global hierarchical path planning of mobile robot based on hybrid genetic particle swarm optimization algorithm. Zhengzhou Daxue Xuebao/Journal of Zhengzhou University, vol. 41, no. 4, pp. 34-40, 2020.
[5]
Wang B, Li S, Guo J, Car-like mobile robot path planning in rough terrain using multi-objective particle swarm optimization algorithm. Neurocomputing, vol. 282, no. 22, pp. 42-51, 2018.
[6]
Tao Q, Sang H, Guo H, Improved Particle Swarm Optimization Algorithm for AGV Path Planning. IEEE Access, no. 99, pp. 1-1, 2021.
[7]
Zhang L, Zhang Y, Li Y. Mobile Robot Path Planning Based on Improved Localized Particle Swarm Optimization. IEEE Sensors Journal, no. 99, pp. 1-1, 2020.
[8]
Ghathwan K I, Mohammed A J, Yusof Y. Optimal Robot Path Planning using Enhanced Particle Swarm Optimization algorithm. Iraqi Journal of Science, vol. 61, no. 1, pp. 178-184, 2020.
[9]
Lian J, Yu W, Xiao K, Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering, vol. 2020, no. 3, pp. 1-20, 2020.
[10]
Alshaikhli O A, Al-Araji A. Path Planning and Control Strategy Design for Mobile Robot Based on Hybrid Swarm Optimization Algorithm. International Journal of Intelligent Engineering and Systems, vol. 14, no. 3, pp. 2021, 2021.
[11]
Xu S, Ho E, Shum H. A HYBRID METAHEURISTIC NAVIGATION ALGORITHM FOR ROBOT PATH ROLLING PLANNING IN AN UNKNOWN ENVIRONMENT. Control & Intelligent Systems, vol. 47, no. 4, pp. 216-224, 2019.
[12]
Yousif M, Salim A, Jummar W K. A Robotic Path Planning by Using Crow Swarm Optimization Algorithm. International Journal of Mathematical Sciences and Computing, vol. 7, no. 1, pp. 20-25, 2021.

Cited By

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  • (2024)Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robotsJournal of Field Robotics10.1002/rob.2233241:5(1426-1437)Online publication date: 5-Apr-2024
  • (2023)Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm OptimizationSustainability10.3390/su15161210115:16(12101)Online publication date: 8-Aug-2023
  • (2023)Autonomous Inspection Method of UHV Substation Robot Based on Deep Learning in Cloud Computing EnvironmentJournal of Circuits, Systems and Computers10.1142/S021812662450088933:05Online publication date: 26-Oct-2023

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cover image ACM Other conferences
ICISCAE 2021: 2021 4th International Conference on Information Systems and Computer Aided Education
September 2021
2972 pages
ISBN:9781450390255
DOI:10.1145/3482632
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 22 November 2021

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Cited By

View all
  • (2024)Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robotsJournal of Field Robotics10.1002/rob.2233241:5(1426-1437)Online publication date: 5-Apr-2024
  • (2023)Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm OptimizationSustainability10.3390/su15161210115:16(12101)Online publication date: 8-Aug-2023
  • (2023)Autonomous Inspection Method of UHV Substation Robot Based on Deep Learning in Cloud Computing EnvironmentJournal of Circuits, Systems and Computers10.1142/S021812662450088933:05Online publication date: 26-Oct-2023

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