Abstract

In this paper, we propose a computationally efficient heuristic solution to choosing a path around obstacles in the face of limited sensor information. Specifically, we propose a navigation algorithm for a mobile robot that reaches a measured target position while avoiding obstacles, making decisions in real-time (without stopping) and relying strictly on information obtained from limited and noisy robot-mounted sensors to determine the location and severity of obstacles. The solution utilizes fuzzy processing to encode the environment – the fuzzy encoding is used both in deciding on an intermediate target direction and in a collision-avoidance strategy. A closed-loop nonlinear feedback control provides a smooth motion with stability guarantees. Simulation results in a corridor environment demonstrate expected collision-free trajectories.

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