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- Krug, Robert, 1981-, et al.
(författare)
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Velvet fingers : grasp planning and execution for an underactuated gripper with active surfaces
- 2014
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Ingår i: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781479936854 ; , s. 3669-3675
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Konferensbidrag (refereegranskat)abstract
- In this work we tackle the problem of planning grasps for an underactuated gripper which enable it to retrieve target objects from a cluttered environment. Furthermore,we investigate how additional manipulation capabilities of the gripping device, provided by active surfaces on the inside of the fingers, can lead to performance improvement in the grasp execution process. To this end, we employ a simple strategy, in which the target object is ‘pulled-in’ towards the palm during grasping which results in firm enveloping grasps. We show the effectiveness of the suggested methods by means of experiments conducted in a real-world scenario.
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- Magnusson, Martin, 1977-, et al.
(författare)
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Beyond points : Evaluating recent 3D scan-matching algorithms
- 2015
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Ingår i: 2015 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781479969234 ; , s. 3631-3637
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Konferensbidrag (refereegranskat)abstract
- Given that 3D scan matching is such a central part of the perception pipeline for robots, thorough and large-scale investigations of scan matching performance are still surprisingly few. A crucial part of the scientific method is to perform experiments that can be replicated by other researchers in order to compare different results. In light of this fact, this paper presents a thorough comparison of 3D scan registration algorithms using a recently published benchmark protocol which makes use of a publicly available challenging data set that covers a wide range of environments. In particular, we evaluate two types of recent 3D registration algorithms - one local and one global. Both approaches take local surface structure into account, rather than matching individual points. After well over 100 000 individual tests, we conclude that algorithms using the normal distributions transform (NDT) provides accurate results compared to a modern implementation of the iterative closest point (ICP) method, when faced with scan data that has little overlap and weak geometric structure. We also demonstrate that the minimally uncertain maximum consensus (MUMC) algorithm provides accurate results in structured environments without needing an initial guess, and that it provides useful measures to detect whether it has succeeded or not. We also propose two amendments to the experimental protocol, in order to provide more valuable results in future implementations.
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