| DOI | Resolve DOI: https://doi.org/10.1109/ICUAS48674.2020.9213964 |
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| Author | Search for: Chen, Long1; Search for: Mantegh, Iraj1; Search for: He, Tong1; Search for: Xie, Wenfang |
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| Affiliation | - National Research Council of Canada. Aerospace
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| Format | Text, Article |
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| Conference | 2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020, Athens, Greece |
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| Subject | fuzzy logic; path planning; collision avoidance; heuristic algorithms; vehicle dynamics; unmanned aerial vehicles; autonomous aerial vehicles; collision avoidance; fuzzy control; mobile robots; robot dynamics; trees (mathematics) |
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| Abstract | Path planning is the essential capability for autonomous navigation of UAV (Unmanned Aerial Vehicle) in unknown environments. In this paper, a Fuzzy logic inferencing system has been designed to achieve obstacle avoidance in a dynamic environment. We introduce Fuzzy-Kinodynamic RRT, method which generates dynamic path based on the traditional rapidly exploring random tree (RRT) algorithm. A set of simple Fuzzy rules are proposed for simple 2D and 3D path planning cases. It is an optimized path planning method which uses Kinodynamic RRT algorithm [1] [2] to do global path planning and utilizes Fuzzy logic to avoid obstacles. A set of heuristics Fuzzy rules are proposed to lead the UAV away from un-modeled ground-based obstacles and to guide the UAV towards the goal. In addition, the designed Fuzzy rules can augment traditional RRT for dealing with new obstacles in the environment. Various simulations are conducted in 2D and 3D environment and the results illustrate the effectiveness of the algorithm in simple dynamic environment. |
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| Publication date | 2020-10-06 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | da33bd0a-bbee-4648-86b3-7ba64b9a917c |
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| Record created | 2022-03-16 |
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| Record modified | 2022-03-16 |
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