AAAI Publications, Twenty-Second International Conference on Automated Planning and Scheduling

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Sampling-Based Coverage Path Planning for Inspection of Complex Structures
Brendan J. Englot, Franz S. Hover

Last modified: 2012-05-14


We present several new contributions in sampling-based coverage path planning, the task of finding feasible paths that give 100% sensor coverage of complex structures in obstaclefilled and visually occluded environments. First, we establish a framework for analyzing the probabilistic completeness of a sampling-based coverage algorithm, and derive results on the completeness and convergence of existing algorithms. Second, we introduce a new algorithm for the iterative improvement of a feasible coverage path; this relies on a samplingbased subroutine that makes asymptotically optimal local improvements to a feasible coverage path based on a strong generalization of the RRT* algorithm. We then apply the algorithm to the real-world task of autonomous in-water ship hull inspection. We use our improvement algorithm in conjunction with redundant roadmap coverage planning algorithm to produce paths that cover complex 3D environments with unprecedented efficiency.


Path Planning; Sensor-Based Planning; Marine Robotics

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