Efficient path planning and trajectory tracking are central to the safe and autonomous navigation of autonomous underwater vehicles (AUVs) in complex and unknown environments. In this paper, we propose an integrated framework that couples enhanced path planning, curvature-adaptive trajectory tracking, and sonar-constrained 3D exploration. First, the path planner is improved by incorporating safety margin-based collision detection, 3D obstacle avoidance weights, and online replanning. Second, the tracking module is enhanced with B-spline optimization and curvature-adaptive speed control to ensure smooth and dynamically feasible trajectories. Third, the exploration strategy is augmented with frontier clustering, multi-dimensional information gain evaluation, and TSP path optimization. Our framework jointly addresses practical constraints including forward-looking sonar field-of-view limitations, safety clearance margins, and the coupling of dynamic replanning with low-level tracking feasibility, while supporting both modular decoupling and integrated collaborative operation. Simulations using ArduSub SITL and Gazebo demonstrate that our integrated approach achieves a superior performance in path safety and tracking accuracy, along with an exploration coverage of 79.08%, validating its effectiveness for robust AUV autonomy in unknown 3D underwater scenarios.
Xiao et al. (Fri,) studied this question.