Abstract
AbstractCrunchBot is a robot platform for developing models of tactile perception and navigation. We present the architecture of CrunchBot, and show why tactile navigation is difficult. We give novel real-time performance results from components of a tactile navigation system and a description of how they may be integrated at a systems level. Components include floor surface classification, radial distance estimation and navigation. We show how tactile-only navigation differs fundamentally from navigation tasks using vision or laser sensors, in that the assumptions about the data preclude standard algorithms (such as extended Kalman Filters) and require brute-force methods.KeywordsMobile RobotLikelihood FunctionExtend Kalman FilterUnscented Kalman FilterNavigation TaskThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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