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- Title
Incorporation of Potential Fields and Motion Primitives for the Collision Avoidance of Unmanned Aircraft.
- Authors
Lee, Kyuman; Choi, Daegyun; Kim, Donghoon
- Abstract
Collision avoidance (CA) using the artificial potential field (APF) usually faces several known issues such as local minima and dynamically infeasible problems, so unmanned aerial vehicles' (UAVs) paths planned based on the APF are safe only in a certain environment. This research proposes a CA approach that combines the APF and motion primitives (MPs) to tackle the known problems associated with the APF. Since MPs solve for a locally optimal trajectory with respect to allocated time, the trajectory obtained by the MPs is verified as dynamically feasible. When a collision checker based on the k-d tree search algorithm detects collision risk on extracted sample points from the planned trajectory, generating re-planned path candidates to avoid obstacles is performed. After rejecting unsafe route candidates, one applies the APF to select the best route among the remaining safe-path candidates. To validate the proposed approach, we simulated two meaningful scenario cases—the presence of static obstacles situation with local minima and dynamic environments with multiple UAVs present. The simulation results show that the proposed approach provides smooth, efficient, and dynamically feasible pathing compared to the APF.
- Subjects
OBSTACLE avoidance (Robotics); SEARCH algorithms; LOCAL government; NOISE control
- Publication
Applied Sciences (2076-3417), 2021, Vol 11, Issue 7, p3103
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app11073103