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In-hand manipulation using gravity and controlled slip
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-3653-4691
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0001-5129-342X
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-3731-0582
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. (CAS)ORCID iD: 0000-0003-2078-8854
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2015 (English)In: Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, IEEE conference proceedings, 2015, 5636-5641 p.Conference paper (Refereed)
Abstract [en]

In this work we propose a sliding mode controllerfor in-hand manipulation that repositions a tool in the robot’shand by using gravity and controlling the slippage of the tool. In our approach, the robot holds the tool with a pinch graspand we model the system as a link attached to the grippervia a passive revolute joint with friction, i.e., the grasp onlyaffords rotational motions of the tool around a given axis ofrotation. The robot controls the slippage by varying the openingbetween the fingers in order to allow the tool to move tothe desired angular position following a reference trajectory.We show experimentally how the proposed controller achievesconvergence to the desired tool orientation under variations ofthe tool’s inertial parameters.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 5636-5641 p.
Keyword [en]
robotics, manipulation, in-hand manipulation, extrinsic dexterity, friction, slip
National Category
URN: urn:nbn:se:kth:diva-178958DOI: 10.1109/IROS.2015.7354177ISI: 000371885405113ScopusID: 2-s2.0-84958153950OAI: diva2:878687
IEEE/RSJ International Conference on Intelligent Robots and Systems
EU, FP7, Seventh Framework Programme, ICT-288533

QC 20160112

Available from: 2015-12-09 Created: 2015-12-09 Last updated: 2016-05-24Bibliographically approved
In thesis
1. Robotic Manipulation under Uncertainty and Limited Dexterity
Open this publication in new window or tab >>Robotic Manipulation under Uncertainty and Limited Dexterity
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Robotic manipulators today are mostly constrained to perform fixed, repetitive tasks. Engineers design the robot’s workcell specifically tailoredto the task, minimizing all possible uncertainties such as the location of tools and parts that the robot manipulates. However, autonomous robots must be capable of manipulating novel objects with unknown physical properties such as their inertial parameters, friction and shape. In this thesis we address the problem of uncertainty connected to kinematic constraints and friction forces in several robotic manipulation tasks. We design adaptive controllers for opening one degree of freedom mechanisms, such as doors and drawers, under the presence of uncertainty in the kinematic parameters of the system. Furthermore, we formulate adaptive estimators for determining the location of the contact point between a tool grasped by the robot and the environment in manipulation tasks where the robot needs to exert forces with the tool on another object, as in the case of screwing or drilling. We also propose a learning framework based on Gaussian Process regression and dual arm manipulation to estimate the static friction properties of objects. The second problem we address in this thesis is related to the mechanical simplicity of most robotic grippers available in the market. Their lower cost and higher robustness compared to more mechanically advanced hands make them attractive for industrial and research robots. However, the simple mechanical design restrictsthem from performing in-hand manipulation, i.e. repositioning of objects in the robot’s hand, by using the fingers to push, slide and roll the object. Researchers have proposed thus to use extrinsic dexterity instead, i.e. to exploit resources and features of the environment, such as gravity or inertial forces,  that can help the robot to perform regrasps. Given that the robot must then interact with the environment, the problem of uncertainty becomes highly relevant. We propose controllers for performing pivoting, i.e. reorienting the grasped object in the robot’s hand, using gravity and controlling the friction exerted by the fingertips by varying the grasping force.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 43 p.
TRITA-CSC-A, ISSN 1653-5723 ; 2016:15
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
urn:nbn:se:kth:diva-187484 (URN)978-91-7729-022-3 (ISBN)
Public defence
2016-06-13, F3, Lindstedtsvägen 26, KTH Campus Valhallavägen, Stockholm, 10:00 (English)

QC 20160524

Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2016-05-30Bibliographically approved

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