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This paper presents DARC, a next generation control framework for robot applications. It is designed to be equally powerful in prototyping research projects and for building serious commercial robots running on low powered embedded hardware, thus closing the gab between research and industry. It incorporates several new techniques such as a decentralized peer-to-peer architecture, transparent network...
In this paper we consider a probabilistic method for extracting terrain maps from a scene and use the information to detect potential navigation obstacles within it. The method uses Gaussian process regression (GPR) to predict an estimate function and its relative uncertainty. To test the new methods, we have arranged two setups: an artificial flat surface with an object in front of the sensors and...
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