Fixed time multi-constraint UAV trajectory planning based on particle swarm optimization
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    Abstract:

    In view of the disadvantage that UAV is usually regarded as a particle in trajectory planning with particle swarm optimization algorithm,the flight time,angle and other parameters of UAV are ignored,a trajectory planning method combining numerical method with particle swarm optimization algorithm was proposed.Firstly,considering that the optimization of each control variable will cost a lot of time,the flight time of UAV was discretized as a certain number of Chebyshev points,and control variables were optimized at these discrete collocations to reduce the computational burden.Secondly,the angular velocity was taken as the control variable,the function of angular velocity and time was solved by curve fitting,and the function of angular and position of UAV with time was obtained by integration.Thirdly,the angular velocity,angle and position were calculated according to the allocated time.Finally,the simulation of UAV trajectory planning in complex environment was carried out,and the effectiveness and feasibility of the proposed method were verified by comparing the Monte-Carlo simulation results with the results of existing methods.The results show that the proposed method can calculate the kinematic parameters including position,plan a smooth trajectory and successfully avoid the obstacles in the process of forward.Therefore,the combination of particle swarm optimization algorithm and numerical method can solve the kinematics parameters of UAV and provide certain reference value for the improvement of the solution dimension of trajectory planning and the realization of intelligent autonomous flight.

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SHAO Shikai, SHI Weilong, DU Yun. Fixed time multi-constraint UAV trajectory planning based on particle swarm optimization[J]. Journal of Hebei University of Science and Technology,2022,43(3):259-267

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History
  • Received:October 14,2021
  • Revised:January 01,2022
  • Adopted:
  • Online: July 08,2022
  • Published: