期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 7, 期 4, 页码 9731-9738出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3191939
关键词
Motion and path planning; optimization and optimal control; service robotics
类别
资金
- Canadian Mitacs Accelerate [IT16435]
- Avidbots Corp., Kitchener, ON, Canada
In this research, we propose a turn-minimizing coverage planning method that can compute the optimal coverage path for a robot operating indoors in polynomial time. By formulating a linear program, we partition the environment into axis-parallel ranks of equal width and compare the results with other approaches.
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 the path by covering the environment along the least number of coverage lines, i.e., straight-line paths. This is because turning not only slows down the robot but also negatively affects the quality of coverage, e.g., tools like cameras and cleaning attachments commonly have poor performance around turns. The problem of minimizing coverage lines however is typically solved using heuristics that do not guarantee optimality. In this work, we propose a turn-minimizing coverage planning method that computes the optimal number of axis-parallel (horizontal/vertical) coverage lines for the environment in polynomial time. We do this by formulating a linear program (LP) that optimally partitions the environment into axis-parallel ranks (non-intersecting rectangles of width equal to the tool width). We then generate coverage paths for a set of real-world indoor environments and compare the results with state-of-the-art coverage approaches.
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