Abstract
This paper presents empirical results of the effect of the global position information on the performance of the modified local navigation algorithm (MLNA) for unknown world exploration. The results show that global position information enables the algorithm to maintain 100% success rate irrespective of initial robot position, movement speed, and environment complexity. Most mobile robot systems accrue an odometry error while moving, and hence need to use external sensors to recalibrate their position on an ongoing basis. We deal with position calibration to compensate the odometry error using the global position information provided by the Teleworkbench, which is a teleoperated platform and test bed for managing experiments using mini-robots. In this paper we demonstrate how we incorporate the global position information during and after the experiments.
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