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

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.(A)

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