Optimal Partitioning of Non-Convex Environments for Minimum Turn Coverage Planning

In this letter, we tackle the problem of planning an optimal coverage path for a robot operating indoors. Many existing approaches attempt to discourage turns in by covering environment along least number coverage lines , i.e., straight-line paths. This is because turning not only slows down but also negatively affects quality coverage, e.g., tools like cameras and cleaning attachments commonly have poor performance around turns. The minimizing lines however typically solved using heuristics that do guarantee optimality. work, propose turn-minimizing method computes axis-parallel (horizontal/vertical) polynomial time. We formulating linear program (LP) optimally partitions into xmlns:xlink="http://www.w3.org/1999/xlink">ranks (non-intersecting rectangles width equal tool width). then generate paths set real-world indoor environments compare results with state-of-the-art approaches.