| 1. |
- Billard, Aude, et al.
(author)
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Trends and challenges in robot manipulation
- 2019
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In: Science. - : American Association for the Advancement of Science. - 0036-8075 .- 1095-9203. ; 364:6446, s. 1149-
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Research review (peer-reviewed)abstract
- Dexterous manipulation is one of the primary goals in robotics. Robots with this capability could sort and package objects, chop vegetables, and fold clothes. As robots come to work side by side with humans, they must also become human-aware. Over the past decade, research has made strides toward these goals. Progress has come from advances in visual and haptic perception and in mechanics in the form of soft actuators that offer a natural compliance. Most notably, immense progress in machine learning has been leveraged to encapsulate models of uncertainty and to support improvements in adaptive and robust control. Open questions remain in terms of how to enable robots to deal with the most unpredictable agent of all, the human.
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| 2. |
- Hang, Kaiyu, 1987-, et al.
(author)
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Hierarchical Fingertip Space : A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation
- 2016
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In: IEEE Transactions on robotics. - : IEEE Press. - 1552-3098 .- 1941-0468. ; 32:4, s. 960-972
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Journal article (peer-reviewed)abstract
- We present a unified framework for grasp planning and in-hand grasp adaptation using visual, tactile and proprioceptive feedback. The main objective of the proposed framework is to enable fingertip grasping by addressing problems of changed weight of the object, slippage and external disturbances. For this purpose, we introduce the Hierarchical Fingertip Space (HFTS) as a representation enabling optimization for both efficient grasp synthesis and online finger gaiting. Grasp synthesis is followed by a grasp adaptation step that consists of both grasp force adaptation through impedance control and regrasping/finger gaiting when the former is not sufficient. Experimental evaluation is conducted on an Allegro hand mounted on a Kuka LWR arm.
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| 4. |
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| 5. |
- Hang, Kaiyu, et al.
(author)
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Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps
- 2014
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Conference paper (other academic/artistic)abstract
- The ability to synthesize and execute fingertip grasps are bases for dexterous in-hand manipulation. Reliable fingertip grasping is difficult to achieve due to noise and uncertainties in object and hand model, as well as hand control etc. Moreover, in many cases it is desirable to employ an adaptive approach that can deal with changed external forces. In this paper, we propose an approach to jointly optimize stability, adaptability, and reachability of grasps using combinatorial optimization for a hierarchical representation of the fingertip space. To illustrate our approach, we demonstrate an example synthesized by the proposed framework and executed by an Allegro hand. We also show how it is adapted when a perturbation is applied.
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| 6. |
- Hang, Kaiyu, et al.
(author)
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On the Evolution of Fingertip Grasping Manifolds
- 2016
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In: IEEE International Conference on Robotics and Automation. - : IEEE Robotics and Automation Society. - 9781467380263 ; , s. 2022-2029
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Conference paper (peer-reviewed)abstract
- Efficient and accurate planning of fingertip grasps is essential for dexterous in-hand manipulation. In this work, we present a system for fingertip grasp planning that incrementally learns a heuristic for hand reachability and multi-fingered inverse kinematics. The system consists of an online execution module and an offline optimization module. During execution the system plans and executes fingertip grasps using Canny’s grasp quality metric and a learned random forest based hand reachability heuristic. In the offline module, this heuristic is improved based on a grasping manifold that is incrementally learned from the experiences collected during execution. The system is evaluated both in simulation and on a SchunkSDH dexterous hand mounted on a KUKA-KR5 arm. We show that, as the grasping manifold is adapted to the system’s experiences, the heuristic becomes more accurate, which results in an improved performance of the execution module. The improvement is not only observed for experienced objects, but also for previously unknown objects of similar sizes.
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| 7. |
- Li, Miao, et al.
(author)
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Dexterous grasping under shape uncertainty
- 2016
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In: Robotics and Autonomous Systems. - : Elsevier. - 0921-8890 .- 1872-793X. ; 75, s. 352-364
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Journal article (peer-reviewed)abstract
- An important challenge in robotics is to achieve robust performance in object grasping and manipulation, dealing with noise and uncertainty. This paper presents an approach for addressing the performance of dexterous grasping under shape uncertainty. In our approach, the uncertainty in object shape is parametrized and incorporated as a constraint into grasp planning. The proposed approach is used to plan feasible hand configurations for realizing planned contacts using different robotic hands. A compliant finger closing scheme is devised by exploiting both the object shape uncertainty and tactile sensing at fingertips. Experimental evaluation demonstrates that our method improves the performance of dexterous grasping under shape uncertainty.
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| 8. |
- Li, Miao, et al.
(author)
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Learning of Grasp Adaptation through Experience and Tactile Sensing
- 2014
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In: IEEE/RSJ International Conference on Intelligent Robots and Systems. - 2153-0858 .- 2153-0866.
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Conference paper (peer-reviewed)abstract
- To perform robust grasping, a multi-fingered robotic hand should be able to adapt its grasping configuration, i.e., how the object is grasped, to maintain the stability of the grasp. Such a change of grasp configuration is called grasp adaptation and it depends on the controller, the employed sensory feedback and the type of uncertainties inherit to the problem. This paper proposes a grasp adaptation strategy to deal with uncertainties about physical properties of objects, such as the object weight and the friction at the contact points. Based on an object-level impedance controller, a grasp stability estimator is first learned in the object frame. Once a grasp is predicted to be unstable by the stability estimator, a grasp adaptation strategy is triggered according to the similarity between the new grasp and the training examples. Experimental results demonstrate that our method improves the grasping performance on novel objects with different physical properties from those used for training.
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| 9. |
- Schmitow, Clara, 1983-, et al.
(author)
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Using a head-mounted camera to infer attention direction
- 2013
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In: International Journal of Behavioral Development. - : SAGE Publications. - 0165-0254 .- 1464-0651. ; 37:5, s. 468-474
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Journal article (peer-reviewed)abstract
- A head-mounted camera was used to measure head direction. The camera was mounted to the forehead of 20 6- and 20 12-month-old infants while they watched an object held at 11 horizontal (−80° to + 80°) and 9 vertical (−48° to + 50°) positions. The results showed that the head always moved less than required to be on target. Below 30° in the horizontal dimension, the head undershoot of object direction was less than 5°. At 80°, however, the undershoot was substantial or between 10° and 15°. In the vertical dimension, the undershoot was larger than in the horizontal dimension. At 30°, the undershoot was around 25% in the downward direction and around 40% in the upward direction. The size of the undershoot was quite consistent between conditions. It was concluded that the head-mounted camera is a useful indicator of horizontal looking direction in a free looking situation where the head is only turned moderately from a straight ahead position.
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