TY - JOUR
T1 - 复杂动态环境下无人飞行器动态避障近似最优轨迹规划
AU - Guo, Hang
AU - Fu, Wen Xing
AU - Fu, Bin
AU - Chen, Kang
AU - Yan, Jie
N1 - Publisher Copyright:
© 2019, Editorial Dept. of JA. All right reserved.
PY - 2019/2/28
Y1 - 2019/2/28
N2 - With regarding to the dynamic obstacle avoidance problem in the dynamic environment encountered by the current unmanned aerial vehicles (UAVs), the kinetics of both the UAV and dynamic obstacles are established on the basis of the appropriate hypothesis, and the terminal constraints, control limitations as well as safe avoidance are taken into consideration. With the minimal energy consumption as the performance index, the dynamic obstacle avoidance problem is described mathematically. Then, with regarding to the terminal constraints and control limitations, an initial trajectory is generated according to the Optimized Model Predictive Static Programming (OMPSP). Against to the inequality constraint resulting from the dynamic obstacle avoidance, the slack variables are introduced and combined with the sliding mode control, and their dynamics are designed to implement the avoidance trajectory for single or multiple dynamic obstacles simultaneously. Eventually, the trajectory is further optimized by Receding Horizontal Differential Dynamic Programming (RHDDP). Consequently, a near optimal trajectory which satisfies multiple constraints and is capable of avoiding dynamic obstacles is developed.
AB - With regarding to the dynamic obstacle avoidance problem in the dynamic environment encountered by the current unmanned aerial vehicles (UAVs), the kinetics of both the UAV and dynamic obstacles are established on the basis of the appropriate hypothesis, and the terminal constraints, control limitations as well as safe avoidance are taken into consideration. With the minimal energy consumption as the performance index, the dynamic obstacle avoidance problem is described mathematically. Then, with regarding to the terminal constraints and control limitations, an initial trajectory is generated according to the Optimized Model Predictive Static Programming (OMPSP). Against to the inequality constraint resulting from the dynamic obstacle avoidance, the slack variables are introduced and combined with the sliding mode control, and their dynamics are designed to implement the avoidance trajectory for single or multiple dynamic obstacles simultaneously. Eventually, the trajectory is further optimized by Receding Horizontal Differential Dynamic Programming (RHDDP). Consequently, a near optimal trajectory which satisfies multiple constraints and is capable of avoiding dynamic obstacles is developed.
KW - Dynamic obstacle avoidance
KW - Near optimal trajectory
KW - Optimized model predictive static programming
KW - Slack variables
KW - Unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85067469378&partnerID=8YFLogxK
U2 - 10.3873/j.issn.1000-1328.2019.02.007
DO - 10.3873/j.issn.1000-1328.2019.02.007
M3 - 文章
AN - SCOPUS:85067469378
SN - 1000-1328
VL - 40
SP - 182
EP - 190
JO - Yuhang Xuebao/Journal of Astronautics
JF - Yuhang Xuebao/Journal of Astronautics
IS - 2
ER -