A mobile robot that autonomously functions in a complex and previously unknown indoor environment has been developed. The omnidirectional mobile robot uses stereo vision, odometry, and contact bumpers to instantiate a symbolic world model. Finding stereo correspondences across a single epipolar line is adequate for instantiating the model. Uncertainty in sensor data is represented by a multivariate normal distribution, and uncertainty models for motion and stereo are presented. Uncertainty is reduced by extended Kalman filtering. To execute a high-level command such as 'Enter the second door on the left', a model is instantiated from sensing and motions are planned and executed. Experimental results from the fast, running system are presented.
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