Title: Subgoal-based local navigation and obstacle avoidance using a grid-distance field

Authors: Anthony S. Maida, Suresh Golconda, Pablo Mejia, Arun Lakhotia, Charles Cavanaugh

Addresses: Centre for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, Louisiana 70504, USA. ' Centre for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, Louisiana 70504, USA. ' Centre for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, Louisiana 70504, USA. ' Centre for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, Louisiana 70504, USA. ' Centre for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, Louisiana 70504, USA

Abstract: The local path-planning and obstacle-avoidance module used in the CajunBot, six-wheeled, all-terrain, autonomous land rover is described. The module is designed for rapid subgoal extraction in service of a global navigation system that follows GPS-supplied waypoints. The core algorithm is built around a grid-based, linear-activation field (a type of artificial potential field). The local path planner has three novel features: the artificial potential field delivers local waypoints, or navigation subgoals, rather than a gradient; the planner aggressively avoids obstacles; and, the algorithm makes use of a repulsive expansion region to compensate for imperfect manoeuvrability.

Keywords: autonomous navigation; GPS navigation; local path planning; obstacle avoidance; local navigation; vehicle autonomous systems; autonomous land rover; artificial potential field; grid-distance field; autonomous vehicles.

DOI: 10.1504/IJVAS.2006.012203

International Journal of Vehicle Autonomous Systems, 2006 Vol.4 No.2/3/4, pp.122 - 142

Available online: 28 Jan 2007 *

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