Abstract
The sensor-based navigation for a mobile robot is a problem of how to select a sequence of sensor-based behaviors between start and goal positions. If a mobile robot does not know its 2-d environment completely or partially, it is obliged to rely on sensor information reflected from closer obstacles in order to avoid them on-line. In the on-line framework, we should consider how a mobile robot reaches its goal position in an uncertain 2-d world. Therefore we will study some previous sensor-based navigation algorithms for mobile robots. Our motivations are to ascertain the convergence of a mobile robot to its goal position, compare the lengths of sensor-based sequences made in the previous algorithms, and decrease the length of a sequence of sensor-based motions, which is generated between start and goal positions by a sensor-feedback obstacle avoidance. Because the mobile robot itself, its sensors, and its environment usually have several uncertainties, it is notable as to how a mobile robot arrives at or near its goal in overcoming such uncertainties. It is demonstrated that the sensor-based navigation still has an enormous potential as an actual navigation of a mobile robot in a completely or partially unknown environment.
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