Rapid Vector-based Any-angle Path Planning with Non-convex Obstacles
Abstract
Vector-based algorithms are novel algorithms in optimal any-angle path planning that are motivated by bug algorithms, bypassing free space by directly conducting line-of-sight checks between two queried points, and searching along obstacle contours if a check collides with an obstacle. The algorithms outperform conventional free-space planners such as A* especially when the queried points are far apart. The thesis presents novel search methods to speed up vector-based algorithms in non-convex obstacles by delaying line-of-sight checks. The "best hull" is a notable method that allows for monotonically increasing path cost estimates even without verifying line-of-sight, utilizing "phantom points" placed on non-convex corners to mimic future turning points. Building upon the methods, the algorithms R2 and R2+ are formulated, which outperform other vector-based algorithms when the optimal path solution is expected to have few turning points. Other novel methods include a novel and versatile multi-dimensional ray tracer for occupancy grids, and a description of the three-dimensional angular sector for future works.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2024
- DOI:
- 10.48550/arXiv.2408.05806
- arXiv:
- arXiv:2408.05806
- Bibcode:
- 2024arXiv240805806L
- Keywords:
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- Computer Science - Robotics;
- Computer Science - Computational Geometry
- E-Print:
- PhD Thesis