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• [P1285] Trajectory Planning for An Unmanned Ground Vehicle Group Using Augmented Particle Swarm Optimization in a Dynamic Environment
  Author(s): Yufang Jin
  
  

  Abstract
  Optimal path planning is a key problem for the control of autonomous unmanned ground vehicles. Particle swarm optimization has been used to solve the optimal problem in the static environment. In this paper a dynamic obstacleavoidance path planning for an unmanned ground vehicle group was considered as optimal problem for shortest path with formation constraints. An augmented Lagrangian particle swarm optimization algorithms was applied to solve this problem. The problem was formulated in Cartesian space with detectable velocity of both the vehicles and obstacles. The fitness function was defined by minimizing the trajectory of the group while keeping the V-shape formation of the group. The simulation results demonstrated that the augmented particle swarm optimization could get the shortest path while keeping the Vformation and converged very fast.

  
   

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