IEEE Transactions on Robotics and Automation · 1995 · 21 citations · 12 references
ComputingComputer ScienceComputer VisionSensorsUncertainty QuantificationPose EstimationUncertainty Estimation3D Pose Estimation6D Object Pose EstimationLeast Squares EstimationObject Pose EstimationPose Estimation Uncertainty
The pose (position and orientation) of a polyhedral object can be determined by using a set of simple light-stripe range sensors. Data from these sensors, however, inherently contains errors which result in pose uncertainty. Therefore, in addition to calculating the pose itself, it is often desirable to estimate how certain the pose determination is. This paper presents a method for estimating the uncertainty in determining the pose of an arbitrarily positioned object with three light-stripe range finders. We analyze the perturbation of a least squares fit of sensed 3D segments to object faces, and obtain a relationship between the sensing error and the object pose error. Experiments demonstrate that the method provides the estimate of accuracy in pose determination.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Active, optical range imaging sensors
Paul J. Besl · Machine Vision and Applications · 1988 · 554 citations