An Info-Centric Trajectory Planner for Unmanned Ground Vehicles

Michael A. Hurni (), Pooya Sekhavat () and I. Michael Ross ()
Additional contact information
Michael A. Hurni: Naval Postgraduate School
Pooya Sekhavat: Naval Postgraduate School
I. Michael Ross: Naval Postgraduate School

Chapter Chapter 11 in Dynamics of Information Systems, 2010, pp 213-232 from Springer

Abstract: Summary 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.

Keywords: Trajectory Planning; Unmanned Ground Vehicle; Rendezvous Point; Vehicle Trajectory; Maneuver Time (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4419-5689-7_11

Ordering information: This item can be ordered from
http://www.springer.com/9781441956897

DOI: 10.1007/978-1-4419-5689-7_11

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().