Automatic model building is a fundamental task in mobile robotics. We present a method for sensor-based exploration of unknown environments by non-holonomic mobile robots. This method proceeds by building a data structure called SRT (Sensor-based Random Tree). The SRT represents a roadmap of the explored area with an associated safe region, and estimates the free space as perceived by the robot during the exploration. The original work proposed in [8] presents two techniques: SRT-Ball and SRT-Star. In this paper, we propose an alternative strategy called SRT-Radial that deals with nonholonomic constraints using two alternative planners named SRT-Extensive and SRT-Goal. We present experimental results to show the performance of the SRT-Radial and both planners.
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