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Sensor based navigation enables a robot to explore an unknown environment and build a map of it, using its sensor information. This is one of the traditional research subjects for mobile robots and many algorithms have been proposed. In this work, we developed some strategies for sensor-based motion planning in unknown environments, based in the rapidly-exploring random trees (RRT) approach. These strategies explore the unknown area in a similar way than the Sensor-based Random Tree (SRT) method and adapt the RRT approach to the local path planning in the free space state associated with the safe region. We named our strategies Local SRRT and Local B SRRT. Experimental results are presented, in order to show the performance of the proposed strategies.

Planificación de movimientos basada en sensores para robots móviles en ambientes desconocidos