3D path planning for artificial intelligence fish based on improved Aalgorithm

Expand
  • Aiming at the issues of poor three -dimensional environmental adaptability,excessive redundant path nodes,and unnatural movement in path planning for artificial intelligence fish in static three-dimensional underwater environments,this study proposes a path planning method that integrates an improved A algorithm with Bézier curve optimization. Firstly,the Chebyshev heuristic function is adopted to optimize the cost calculation for diagonal movements in three-dimensional space, thereby enhancing the algorithm's adaptability to such environments. Secondly,an accurate collision detection mechanism based on triangular meshes is introduced to ensure collision-free paths while significantly simplifying path nodes. Finally,quadratic Bézier curves are applied at turning points for local smoothing, generating trajectories that align with the swimming characteristics of fish. The results demonstrate that, while ensuring path safety, tests conducted in static underwater environments with rocky areas and seaweed-coral zones show that the improved algorithm reduces the average path length by 9. 9% ,significantly decreases the number of turning points by 71. 5% ,and markedly enhances path smoothness. This approach effectively overcomes the limitations of traditional A algorithms,such as excessive turns and discontinuous motion,providing an efficient and realistic three-dimensional motion planning solution for artificial intelligence fish.

Online published: 2026-02-09

Cite this article

SONG Yilong1 , CHEN Ming1 , JIN Qing2 , et al . 3D path planning for artificial intelligence fish based on improved Aalgorithm[J]. Fishery Modernization, 2026 , 53(1) : 144 -151 . DOI: 10.26958/j.cnki.1007-9580.2026.01.013

Outlines

/