TY - GEN
T1 - Sample-based Fixed-wing UAV Obstacle Avoidance Method
AU - Zhang, Houxin
AU - Hu, Jinwen
AU - Zhao, Chunhui
AU - Hou, Xiaolei
AU - Xu, Zhao
AU - Guo, Kexin
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/9
Y1 - 2020/10/9
N2 - Compared with the quadrotors, the fixed-wing unmanned aerial vehicles (UAVs) have additional flight constraints such as minimum turning radius, minimum flight speed, and maximum climb rate, which makes it challenging to design obstacle avoidance algorithms for the fixed-wing UAVs. In this paper, we present a novel method to generate a collision-free path based on the Dubins kinetic model. The Monte Carlo sampling algorithm is adopted to solve the optimization problem of the non-analytic path. And the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is utilized to optimize the sampling area for accelerating the solving process. Further, an evaluation function is designed which includes the task-performing efficiency and the fuel consumption to get the optimal flight path. Finally, the simulation results demonstrate the effectiveness of the proposed method.
AB - Compared with the quadrotors, the fixed-wing unmanned aerial vehicles (UAVs) have additional flight constraints such as minimum turning radius, minimum flight speed, and maximum climb rate, which makes it challenging to design obstacle avoidance algorithms for the fixed-wing UAVs. In this paper, we present a novel method to generate a collision-free path based on the Dubins kinetic model. The Monte Carlo sampling algorithm is adopted to solve the optimization problem of the non-analytic path. And the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is utilized to optimize the sampling area for accelerating the solving process. Further, an evaluation function is designed which includes the task-performing efficiency and the fuel consumption to get the optimal flight path. Finally, the simulation results demonstrate the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85098090100&partnerID=8YFLogxK
U2 - 10.1109/ICCA51439.2020.9264439
DO - 10.1109/ICCA51439.2020.9264439
M3 - 会议稿件
AN - SCOPUS:85098090100
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 973
EP - 978
BT - 2020 IEEE 16th International Conference on Control and Automation, ICCA 2020
PB - IEEE Computer Society
T2 - 16th IEEE International Conference on Control and Automation, ICCA 2020
Y2 - 9 October 2020 through 11 October 2020
ER -