Path Planning for UAV-Ship Collaborative Search and Rescue Considering Ship Dynamics

DOI: https://doi.org/10.62517/jes.202602306

Author(s)

Rongjie Tang

Affiliation(s)

School of Navigation, Dalian Maritime University, Dalian, Liaoning, China

Abstract

To address the challenge posed by the dynamic movement of the mother ship to the safety of UAV return-to-base operations during maritime search and rescue, this study proposes a UAV-ship collaborative search and rescue path planning method that incorporates ship motion prediction. At the modeling level, a collaborative search model was constructed that integrates gridded sea areas, target probability updates, anisotropic wind resistance energy consumption, and ship dynamic takeoff and landing window constraints.At the algorithmic level, an Improved Coati Optimization Algorithm(ICOA) was designed, integrating dynamic adversarial learning initialization and covariance matrix guidance, and incorporating an exponential penalty function mechanism based on safety margins. Simulation results show that in static scenarios, PSO performs best (detection probability 0.0283), while ICOA ranks in the middle;in dynamic scenarios, the proposed method improves the safety margin from -470.02 to -0.13 (p < 0.001), whereas the scheme that does not account for vessel movement results in 30 crashes into the sea. Ablation experiments validate the independent contributions of each improvement. The proposed method demonstrates significant advantages in both search and rescue effectiveness and flight safety.

Keywords

Maritime Search and Rescue; UAV Path Planning; IMPROVED Coati Optimization Algorithm; Dynamic Return-to-home Constraint

References

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