摘要
This paper presents online motion planning for UAV(unmanned aerial vehicle) in complex threat field,including both static threats and moving threats,which can be formulated as a dynamic constrained optimal control problem.Receding horizon control(RHC) based on differential evolution(DE) algorithm is adopted.A location-predicting model of moving threats is established to assess the value of threat that UAV faces in flight.Then flyable paths can be generated by the control inputs which are optimized by DE under the guidance of the objective function.Simulation results demonstrate that the proposed method not only generates smooth and flyable paths,but also enables UAV to avoid threats efficiently and arrive at destination safely.
This paper presents online motion planning for UAV（unmanned aerial vehicle） in complex threat field,including both static threats and moving threats,which can be formulated as a dynamic constrained optimal control problem.Receding horizon control（RHC） based on differential evolution（DE） algorithm is adopted.A location-predicting model of moving threats is established to assess the value of threat that UAV faces in flight.Then flyable paths can be generated by the control inputs which are optimized by DE under the guidance of the objective function.Simulation results demonstrate that the proposed method not only generates smooth and flyable paths,but also enables UAV to avoid threats efficiently and arrive at destination safely.
出处
《机器人》
EI
CSCD
北大核心
2013年第1期107-114,共8页
Robot
基金
National Science Fund for Distinguished Young Scholars(60925011)
关键词
无人机
在线运动规划
动态约束
目标函数
unmanned aerial vehicle
motion planning
receding horizon control
differential evolution
