Sampling-Based Coverage Path Planning for Inspection of Complex Structures


  • Brendan Englot Massachusetts Institute of Technology
  • Franz Hover Massachusetts Institute of Technology



Path Planning, Sensor-Based Planning, Marine Robotics


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.




How to Cite

Englot, B., & Hover, F. (2012). Sampling-Based Coverage Path Planning for Inspection of Complex Structures. Proceedings of the International Conference on Automated Planning and Scheduling, 22(1), 29-37.