Space‐Aware Adaptive Trajectory Planning for High Coverage Inspection of Underwater Long‐Range Tunnels

The inspection of long‐range tunnels has become an important challenge in underwater robotics, as it involves a trade‐off among coverage, efficiency, and an energy‐related cost metric. In this paper, we propose a space‐aware trajectory planning algorithm to generate high‐coverage inspection trajectories for long‐range tunnel inspection. The proposed method has distinctive features in the following aspects: (1) three‐dimensional modelling and initial trajectory generation of tunnel structure based on spatial perception; (2) an adaptive spiral trajectory model in cylindrical coordinates to alleviate blind spot problems near tunnel ends; (3) a multi‐objective optimisation strategy based on the non‐dominated sorting genetic algorithm II (NSGA‐II) to balance coverage effectiveness, trajectory smoothness, and energy‐related cost. Simulations in representative tunnel environments demonstrate that the proposed method achieves high coverage rates while substantially reducing redundant motion. These results highlight both the theoretical and practical value of the framework for intelligent tunnel inspection, with promising implications for enhancing the safety of large‐scale water infrastructure.