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Volume 45 Issue 5
May  2023
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ZHAO Taifei, ZHANG Jianwei, RONG Kaixin, ZHANG Wen. Collision Avoidance Algorithm for UAV Formation Reconfiguration under UV Non-uniform Virtual Potential Field[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1651-1659. doi: 10.11999/JEIT220442
Citation: ZHAO Taifei, ZHANG Jianwei, RONG Kaixin, ZHANG Wen. Collision Avoidance Algorithm for UAV Formation Reconfiguration under UV Non-uniform Virtual Potential Field[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1651-1659. doi: 10.11999/JEIT220442

Collision Avoidance Algorithm for UAV Formation Reconfiguration under UV Non-uniform Virtual Potential Field

doi: 10.11999/JEIT220442
Funds:  The National Natural Science Foundation of China (61971345), The Key R & D Plan of Shaanxi Province (2021GY-044), Xi’an Beilin District Science and Technology Plan (GX1921), Yulin Science and Technology Project (2019-145), Xi’an Science Planning Project (CXY1835(4))
  • Received Date: 2022-04-13
  • Accepted Date: 2022-08-25
  • Rev Recd Date: 2022-08-23
  • Available Online: 2022-08-30
  • Publish Date: 2023-05-10
  • To address the path planning and inter-aircraft collision avoidance problems in Unmanned Aerial Vehicle (UAV) formation reconstruction in complex electromagnetic environment, the repulsion function is improved by using distance factor on the basis of traditional UV virtual potential field, and a non-uniform UV virtual potential field is constructed to assist UAVs in collision avoidance in this paper. The improved UV non-uniform virtual potential field can make the collision avoidance path of UAV smoother, and the UAV can fly a longer distance in the same time. In addition, the distance between UAVs is calculated by the wireless ultraviolet ranging method, and the traditional artificial potential field method is improved by combining the ultraviolet non-uniform potential field to realize the formation reconstruction of UAVs. Simulation results show that this algorithm can effectively solve the path oscillation and local minimum problems under the traditional algorithm, while the collision avoidance efficiency is significantly improved compared with the traditional artificial potential field algorithm, and the distance is shortened by 6% in the preset environment while the time to reach the target point is advanced by 40%. The results show that the algorithm can effectively achieve the expected inter-aircraft collision avoidance effect in UAV formation reconstruction.
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