An Info-Centric Trajectory Planner for Unmanned Ground Vehicles

  • Michael A. Hurni
  • Pooya Sekhavat
  • I. Michael Ross
Part of the Springer Optimization and Its Applications book series (SOIA, volume 40)


We present a pseudospectral (PS) optimal control framework for autonomous trajectory planning and control of an Unmanned Ground Vehicle (UGV) with real-time information updates. The algorithm is introduced and implemented on a collection of motion planning scenarios with varying levels of information. The UGV mission is to traverse from an initial start point and reach the target point in minimum time, with maximum robustness, while avoiding both static and dynamic obstacles. This is achieved by computing the control solution that solves the initial planning problem by minimizing a cost function while satisfying dynamical and environmental constraints based on the initial global knowledge of the area. To overcome the problem of incomplete global knowledge and a dynamic environment, the UGV uses its sensors to map the locally detected changes in the environment and continuously updates its global map. At each information update, the optimal control is recomputed and implemented. Simulation results illustrate the performance of the planner under varying levels of information.


Trajectory Planning Unmanned Ground Vehicle Rendezvous Point Vehicle Trajectory Maneuver Time 


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Michael A. Hurni
    • 1
  • Pooya Sekhavat
    • 1
  • I. Michael Ross
    • 1
  1. 1.Naval Postgraduate SchoolMontereyUSA

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