Trajectory Optimization Using Virtual Motion Camouflage and Particle Swarm Optimization

  • Dong Jun Kwak
  • Byunghun Choi
  • H. Jin Kim
Conference paper

DOI: 10.1007/978-3-642-40852-6_60

Volume 8102 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Kwak D.J., Choi B., Kim H.J. (2013) Trajectory Optimization Using Virtual Motion Camouflage and Particle Swarm Optimization. In: Lee J., Lee M.C., Liu H., Ryu JH. (eds) Intelligent Robotics and Applications. ICIRA 2013. Lecture Notes in Computer Science, vol 8102. Springer, Berlin, Heidelberg

Abstract

This paper investigates a new numerical method to solve a nonlinear constrained trajectory optimization problem. Especially, we consider a problem constrained on the terminal angle and time. The proposed algorithm is based on the virtual motion camouflage (VMC) and particle swarm optimization (PSO) and is called VMCPSO. VMC changes the typical full space optimal problem to the subspace optimal problem, so it can reduce the dimension of the original problem by using path control parameters (PCPs). If the PCPs are optimized, then the optimal path can be obtained. Therefore, we employ PSO to optimize these PCPs. The optimization results show that the optimal path considering the terminal angle and time is effectively generated using VMCPSO.

Keywords

Trajectory optimization virtual motion camouflage particle swarm optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dong Jun Kwak
    • 1
  • Byunghun Choi
    • 1
  • H. Jin Kim
    • 1
  1. 1.School of Mechanical and Aerospace EngineeringSeoul National UniversitySeoulKorea