A Path Planning Method for Underwater Robotic Fish 
Considering Perception and Communication Constraints

Yixin Zhang; Xuhong Huang; Weixuan Zhan; Jinghui Lin; Yuanhai Chen

doi:10.70711/aitr.v3i7.8870

A Path Planning Method for Underwater Robotic Fish Considering Perception and Communication Constraints

Yixin Zhang, Xuhong Huang, Weixuan Zhan, Jinghui Lin, Yuanhai Chen

Abstract

With the advancement of underwater automation, robotic fish have been widely applied in marine observation and environmental
monitoring. Coverage Path Planning (CPP) is a key technology affecting the efficiency of autonomous underwater operations. To address the
limitations of traditional methods in complex environments, including poor obstacle adaptability, path redundancy, and high energy consumption, this paper proposes an environment-aware adaptive coverage path planning method for underwater robotic fish. The method integrates
real-time sonar or visual sensing with adaptive grid partitioning and local path optimization to achieve efficient coverage in unknown or semiunknown environments. Simulation results show that the proposed method effectively reduces path length and turning frequency while ensuring full coverage, thereby significantly improving energy efficiency and environmental adaptability.

Keywords

Underwater robotic fish; Covering path planning; Environmental perception; Adaptive planning; Path optimization

Full Text:

PDF

Included Database

References

[1] Li, S., Chang, S., Shi, H., et al. Research on complete coverage path planning for multi-robot systems. Journal of Changchun University

of Technology, 2025, 46(6): 507512. DOI: 10.15923/j.cnki.cn22-1382/t.2025.6.04.

[2] Zhang, Y. Complete coverage path planning method for unmanned aerial vehicles in unknown building environments. Master's Thesis,

Guangdong University of Technology, 2025. DOI: 10.27029/d.cnki.ggdgu.2025.000694.

[3] Wang, N., Wu, H., Zhang, Y. Coverage path planning for unmanned surface vehicles considering maneuvering constraints. Chinese

Journal of Ship Research, 2024, 19(6): 210218. DOI: 10.19693/j.issn.1673-3185.03404.

[4] Cui, B., Lv, Y., Qin, W., et al. Region decomposition and coverage path planning for complex task areas. Unmanned Systems Technology, 2024, 7(1): 97105. DOI: 10.19942/j.issn.2096-5915.2024.01.09.

[5] Shi, C. Research on complete coverage path planning for cleaning robots in complex environments. Master's Thesis, Anhui University

of Science and Technology, 2024. DOI: 10.26918/d.cnki.ghngc.2024.000074.

[6] Sun, W., Luo, Z., Shi, J., et al. A survey of coverage path planning methods for unmanned aerial vehicles. Control Theory & Applications, online first, 2026: 121 [Accessed Jan. 17, 2026].

[7] Lu, J. Research on autonomous exploration mapping and complete coverage path planning algorithms for multi-robot systems. PhD

Thesis, Guangdong University of Technology, 2024. DOI: 10.27029/d.cnki.ggdgu.2024.002784.

[8] Ma, M. Research on hybrid coverage path planning for mobile robots based on map geometric features. Master's Thesis, Guangdong

University of Technology, 2024. DOI: 10.27029/d.cnki.ggdgu.2024.003244.

[9] Qi, L., Hua, Z., Su, H., et al. Online complete coverage path planning for robots in complex desert terrains. Control and Decision, 2024,

39(4): 10951103. DOI: 10.13195/j.kzyjc.2022.1518.

[10] Chen, K., Xie, Y., Li, Y., et al. Complete coverage path planning for agricultural machinery under multi-constraint conditions. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(5): 1726, 43.

[11] Jiang, L., Zhang, Y., Ma, X., et al. Complete coverage path planning based on secondary region decomposition. Journal of Harbin Engineering University, 2022, 43(10): 14831490.

[12] He, L., Liu, X., Huang, T., et al. Research on complete coverage path planning algorithms for mobile robots. Machinery Design & Manufacture, 2021(3): 280284. DOI: 10.19356/j.cnki.1001-3997.2021.03.064.

DOI: http://dx.doi.org/10.70711/aitr.v3i7.8870

Refbacks

There are currently no refbacks.