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We present a lifelong mapping and localisation system for long-term autonomous operation of mobile robots in changing environments. The core of the system is a spatio-temporal occupancy grid that explicitly represents the persistence and periodicity of the individual cells and can predict the probability of their occupancy in the future. During navigation, our robot builds temporally local maps and...
This letter presents an exploration method that allows mobile robots to build and maintain spatio-temporal models of changing environments. The assumption of a perpetually changing world adds a temporal dimension to the exploration problem, making spatio-temporal exploration a never-ending, life-long learning process. We address the problem by application of information-theoretic exploration methods...
We present a real-time visual-based road following method for mobile robots in outdoor environments. The approach combines an image processing method, that allows to retrieve illumination invariant images, with an efficient path following algorithm. The method allows a mobile robot to autonomously navigate along pathways of different types in adverse lighting conditions using monocular vision. To...
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