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article · Journal of Marine Science and Engineering · 2023

Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization

Changyu Lu, Jianmin Yang, Bernt J. Leira, Qihang Chen, Shulin Wang

Cited by 15Open access

Abstract

Three-dimensional path planning is instrumental in path decision making and obstacle avoidance for deep-sea mining vehicles (DSMV). However, conventional particle swarm algorithms have been prone to trapping in local optima and have slow convergence rates when applied to underwater robot path planning. In order to secure a safe and economical three-dimensional path for the DSMV from the mining area to the storage base in connection with innovative mining system, this paper proposes a multi-objective optimization algorithm based on improved particle swarm optimization (IPSO) path planning. Firstly, we construct an unstructured seabed mining area terrain model with hazardous obstacles. Consequently, by considering optimization objectives such as the path length, terrain undulation, comprehensive energy consumption, and crawler slippage rate, we convert the path planning problem into a multi-objective optimization problem, constructing a multi-objective optimization mathematical model. Following that, we propose an IPSO algorithm to tackle the multi-objective non-linear optimization problem, which enables global optimization for DSMV path planning. Finally, we conduct a comprehensive set of experiments using the MATLAB simulation platform and compare the proposed method with existing advanced methods. Experimental results indicate that the path planned by the IPSO exhibits superior performance in terms of path length, terrain undulation, energy consumption, and safety.

Cite this paper

APA 7

Lu, C., Yang, J., Leira, B. J., Chen, Q., & Wang, S. (2023). Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization. Journal of Marine Science and Engineering, 11(9), 1797. https://doi.org/10.3390/jmse11091797

MLA 9

Lu, Changyu, et al. “Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization.” Journal of Marine Science and Engineering, vol. 11, no. 9, 2023, p. 1797, https://doi.org/10.3390/jmse11091797.

Chicago

Lu, Changyu, Jianmin Yang, Bernt J. Leira, Qihang Chen, and Shulin Wang. 2023. “Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization.” Journal of Marine Science and Engineering 11 (9): 1797. https://doi.org/10.3390/jmse11091797.

Harvard

Lu, C. et al. (2023) ‘Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization’, Journal of Marine Science and Engineering, 11(9), p. 1797. Available at: https://doi.org/10.3390/jmse11091797.

BibTeX
@article{lu2023three,
  title = {{Three-Dimensional Path Planning of Deep-Sea Mining Vehicle Based on Improved Particle Swarm Optimization}},
  author = {Lu, Changyu and Yang, Jianmin and Leira, Bernt J. and Chen, Qihang and Wang, Shulin},
  journal = {Journal of Marine Science and Engineering},
  volume = {11},
  number = {9},
  pages = {1797},
  year = {2023},
  doi = {10.3390/jmse11091797}
}

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