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Dynamically Estimating Pose from Invariant Feature Measurements (Baird, 94)

Author: Duncan Baird
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Abstract: Complex robotic tasks such as autonomous exploration and grasping demand the co-operation of sensors and actuators. In order to integrate sensor measurements and actuator control schemes we must determine the rigid body transformations that relate the native co-ordinate frames of these devices. Equivalently, we need to estimate the relative pose of sensors and actuators in the system.

We examine the problem of determining the pose of a robot-mounted range-finding camera, and present a class of solutions motivated by the idea that mobile camera calibration is best addressed by an ongoing dynamic estimation process. We use range measurements and known robot kinematics to provide the estimate of camera pose which is maximally consistent with the available data. Our scheme uses scene features that are often present in typical workcell scenes and that are easily and reliably extracted. We develop several formulations of the principle, and present experimental results for both simulated and real data sets.


next up previous backarrow_motif.gifBack to APL Home Page
Next: Monocular Optical Flow for Up: Available Titles and Abstracts Previous: Active Object Recognition Conditioned
Gilbert Soucy
2000-04-05