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High-speed navigation of unmanned ground vehicles on uneven terrain using potential fields

Published online by Cambridge University Press:  18 January 2007

Shingo Shimoda ,
Yoji Kuroda  and
Karl Iagnemma
Shingo Shimoda*
Affiliation:
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Biomimetic Control Research Center, RIKEN, Nagoya 463-0003, Japan
Yoji Kuroda
Affiliation:
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Karl Iagnemma
Affiliation:
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
*
*Corresponding author. E-mail: [email protected]
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Summary

Many applications require unmanned ground vehicles (UGVs) to travel at high speeds on sloped, natural terrain. In this paper, a potential field-based method is proposed for UGV navigation in such scenarios. In the proposed approach, a potential field is generated in the two-dimensional “trajectory space” of the UGV path curvature and longitudinal velocity. In contrast to traditional potential field methods, dynamic constraints and the effect of changing terrain conditions can be easily expressed in the proposed framework. A maneuver is chosen within a set of performance bounds, based on the local potential field gradient. It is shown that the proposed method is subject to local maxima problems, rather than local minima. A simple randomization technique is proposed to address this problem. Simulation and experimental results show that the proposed method can successfully navigate a small UGV between predefined waypoints at speeds up to 7.0 m/s, while avoiding static hazards. Further, vehicle curvature and velocity are controlled during vehicle motion to avoid rollover and excessive side slip. The method is computationally efficient, and thus suitable for onboard real-time implementation.

Keywords

Mobile robotsPotential fieldsOutdoor terrainMotion planning
Type
Article
Information
Robotica , Volume 25 , Issue 4 , July 2007 , pp. 409 - 424
Copyright
Copyright © Cambridge University Press 2007

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