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The author suggests that to operate efficiently, a robot system must be able to represent, account for, and reason about the effects of uncertainty in areas in which geometric analysis also plays an important part. He proposed that uncertainty be represented as an intrinsic part of all geometric descriptions. Toward this goal he develops a description of uncertain geometric features as families of parametrized functions together with a distribution function defined on the associated parameter vector. Uncertain points, curves, and surfaces are considered, and it is shown how they can be manipulated and transformed between coordinate frames in an efficient and consistent manner. The effectiveness of these techniques is demonstrated by application to the problem of developing maximal-information sensing strategies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Hugh Durrant‐Whyte (1988) studied this question.
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