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Velocity Obstacle Based 3D Collision Avoidance Scheme for Low-Cost Micro UAVs

Author

Listed:
  • Myungwhan Choi

    (Department of Computer Science and Engineering, Sogang University, Seoul 04107, Korea)

  • Areeya Rubenecia

    (Department of Computer Science and Engineering, Sogang University, Seoul 04107, Korea)

  • Taeshik Shon

    (Division of Information and Computer Engineering, Ajou University, Suwon 16499, Korea)

  • Hyo Hyun Choi

    (Department of Computer Science, Inha Technical College, Incheon 22212, Korea)

Abstract

An unmanned aerial vehicle (UAV) must be able to safely reach its destination even, when it can only gather limited information about its environment. When an obstacle is detected, the UAV must be able to choose a path that will avoid collision with the obstacle. For the collision avoidance scheme, we apply the velocity obstacle approach since it is applicable even with the UAV’s limited sensing capability. To be able to apply the velocity obstacle approach, we need to know the parameter values of the obstacle such as its size, current velocity and current position. However, due to the UAV’s limited sensing capability, such information about the obstacle is not available. Thus, by evaluating sensor readings, we get the changes in the possible positions of the obstacle in order to generate the velocity obstacle and make the UAV choose a collision-free trajectory towards the destination. We performed simulation on different obstacle movements and the collision-free trajectory of the UAV is shown in the simulation results.

Suggested Citation

  • Myungwhan Choi & Areeya Rubenecia & Taeshik Shon & Hyo Hyun Choi, 2017. "Velocity Obstacle Based 3D Collision Avoidance Scheme for Low-Cost Micro UAVs," Sustainability, MDPI, vol. 9(7), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1174-:d:103829
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    Cited by:

    1. Guotao Xie & Xinyu Zhang & Hongbo Gao & Lijun Qian & Jianqiang Wang & Umit Ozguner, 2017. "Situational Assessments Based on Uncertainty-Risk Awareness in Complex Traffic Scenarios," Sustainability, MDPI, vol. 9(9), pages 1-17, September.
    2. Alia Ghaddar & Ahmad Merei, 2020. "EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs," Future Internet, MDPI, vol. 12(2), pages 1-20, February.

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