Consider a robot to measure or operate on man made objects randomly located in the workspace. The optronic sensing onboard the robot are a scanning range measuring time-of-flight laser and a CCD camera. The goal of the paper is to give explicit covariance matrices for the extracted geometric primitives in the surrounding workspace. Emphasis is on correlation properties of the stochastic error models during motion. Topics studied include: (i) covariance of Radon/Hough peaks for plane surfaces; (ii) covariances for the intersection of two planes; (iii) equations for combining vision features, plane surfaces and range discontinuities; and (iv) explicit equations of how the covariance matrices are transformed during the robot motion. Typical applications are; models for verification and updating of CAD-models when navigating inside buildings and industrial plants, and accumulating sensor readings for a telecommanded robot
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