Dynamic Free-Space Roadmap for Safe Quadrotor Motion Planning
April 20, 2022 Β· Declared Dead Β· π IEEE/RJS International Conference on Intelligent RObots and Systems
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Authors
Junlong Guo, Zhiren Xun, Shuang Geng, Yi Lin, Chao Xu, Fei Gao
arXiv ID
2204.09265
Category
cs.RO: Robotics
Citations
5
Venue
IEEE/RJS International Conference on Intelligent RObots and Systems
Last Checked
4 months ago
Abstract
Free-space-oriented roadmaps typically generate a series of convex geometric primitives, which constitute the safe region for motion planning. However, a static environment is assumed for this kind of roadmap. This assumption makes it unable to deal with dynamic obstacles and limits its applications. In this paper, we present a dynamic free-space roadmap, which provides feasible spaces and a navigation graph for safe quadrotor motion planning. Our roadmap is constructed by continuously seeding and extracting free regions in the environment. In order to adapt our map to environments with dynamic obstacles, we incrementally decompose the polyhedra intersecting with obstacles into obstacle-free regions, while the graph is also updated by our well-designed mechanism. Extensive simulations and real-world experiments demonstrate that our method is practically applicable and efficient.
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