TY - GEN
T1 - A Compound Online Local Path Planning and Situation-Aware Dynamic Obstacle Avoidance System for UAV
AU - Feng, Yongming
AU - Jin, Ming
AU - Li, Ang
AU - Pan, Fengxing
AU - Zhou, Yaoming
N1 - Publisher Copyright:
© 2024, Chinese Society of Aeronautics and Astronautics.
PY - 2024
Y1 - 2024
N2 - In this paper, a composite system of Unmanned Aerial Vehicles (UAVs) including path planning and dynamic obstacle avoidance is proposed. The system can deal with complex low-altitude environments, achieve autonomous flight path planning, and dynamically avoid obstacles. When obstacles were detected at a relatively far distance, a local collision-free flight path near the affected route is planned online using a plant growth algorithm proposed without changing the current flight state of the UAV. When a moving obstacle suddenly enters the UAV’s flight path at a closer distance, a situation-aware dynamic obstacle avoidance algorithm based on artificial potential fields is preferentially activated to respond at the fastest speed. Meanwhile, the local planner is also used to plan a new local collision-free path again, ensuring the UAV’s flight safety to the greatest extent with minimal cost. The effectiveness of the intelligent UAV composite path planning and dynamic obstacle avoidance system is demonstrated in simulation environment and real-world experiments.
AB - In this paper, a composite system of Unmanned Aerial Vehicles (UAVs) including path planning and dynamic obstacle avoidance is proposed. The system can deal with complex low-altitude environments, achieve autonomous flight path planning, and dynamically avoid obstacles. When obstacles were detected at a relatively far distance, a local collision-free flight path near the affected route is planned online using a plant growth algorithm proposed without changing the current flight state of the UAV. When a moving obstacle suddenly enters the UAV’s flight path at a closer distance, a situation-aware dynamic obstacle avoidance algorithm based on artificial potential fields is preferentially activated to respond at the fastest speed. Meanwhile, the local planner is also used to plan a new local collision-free path again, ensuring the UAV’s flight safety to the greatest extent with minimal cost. The effectiveness of the intelligent UAV composite path planning and dynamic obstacle avoidance system is demonstrated in simulation environment and real-world experiments.
KW - Dynamic Obstacle Avoidance
KW - Intelligent UAV
KW - Path Planning
UR - https://www.scopus.com/pages/publications/85180813346
U2 - 10.1007/978-981-99-8867-9_42
DO - 10.1007/978-981-99-8867-9_42
M3 - 会议稿件
AN - SCOPUS:85180813346
SN - 9789819988662
T3 - Lecture Notes in Mechanical Engineering
SP - 433
EP - 443
BT - Proceedings of the 6th China Aeronautical Science and Technology Conference - Volume 3
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th China Aeronautical Science and Technology Conference, CASTC 2023
Y2 - 26 September 2023 through 27 September 2023
ER -