Three-Dimensional Pose Estimation and Segmentation Methods

Wöhler, Christian

doi:10.1007/978-1-4471-4150-1_2

Cited by 2 publications

(1 citation statement)

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“…The literature dealing with shape detection, pose estimation, and geometry identification problems is substantial (see, for example, Wöhler ()). “What is it?” and “Where is it?” questions, often arise in manufacturing contexts in which manipulation of components requires knowledge of “where” an object is, and process decisions depend on “what” an object is.…”

Section: Background Ideas and Related Workmentioning

confidence: 99%

Is It What I Think It Is? Is It Where I Think It Is? Using Point-Clouds for Diagnostic Testing of a Digging Assembly's Form and Pose for an Autonomous Mining Shovel

2016

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This paper addresses the problem of verifying a control system's knowledge about the shape and pose of an electric mining shovel's digging assembly. The need for such verification arises in order to ensure safe autonomous operation. The likelihood of unintended collision is reduced by confirming that the digging assembly occupies the region of space it is thought to occupy. We present two methods for verification. The first computes the probability that regions of key interest have the geometric form expected, subject to an allowed uncertainty, given measured point-cloud data. The second computes a likelihood distribution over a family of possible hypotheses by considering the level of support each range measurement provides to each hypothesis. The ideas presented extend, with appropriate adaptation, to other applications where it is necessary to verify the knowledge that a control system may possess about regions of space that are occupied from instant-to-instant. C

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Section: Background Ideas and Related Workmentioning

confidence: 99%