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An Adaptive Control Approach for Opening Doors and Drawers Under Uncertainties
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. Chalmers, Sweden.ORCID iD: 0000-0001-5129-342X
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2078-8854
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: 0000-0002-7714-928X
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2016 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 32, no 1, 161-175 p.Article in journal (Refereed) PublishedText
Abstract [en]

We study the problem of robot interaction with mechanisms that afford one degree of freedom motion, e.g., doors and drawers. We propose a methodology for simultaneous compliant interaction and estimation of constraints imposed by the joint. Our method requires no prior knowledge of the mechanisms' kinematics, including the type of joint, prismatic or revolute. The method consists of a velocity controller that relies on force/torque measurements and estimation of the motion direction, the distance, and the orientation of the rotational axis. It is suitable for velocity controlled manipulators with force/torque sensor capabilities at the end-effector. Forces and torques are regulated within given constraints, while the velocity controller ensures that the end-effector of the robot moves with a task-related desired velocity. We give proof that the estimates converge to the true values under valid assumptions on the grasp, and error bounds for setups with inaccuracies in control, measurements, or modeling. The method is evaluated in different scenarios involving opening a representative set of door and drawer mechanisms found in household environments.

Place, publisher, year, edition, pages
IEEE , 2016. Vol. 32, no 1, 161-175 p.
Keyword [en]
Adaptive control, calibration and identification, force/motion control, service robots, uncertain kinematics
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-184046DOI: 10.1109/TRO.2015.2506154ISI: 000370764000012ScopusID: 2-s2.0-84961994390OAI: oai:DiVA.org:kth-184046DiVA: diva2:914309
Note

QC 20160323

Available from: 2016-03-23 Created: 2016-03-22 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.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2016:15
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
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)
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Supervisors
Note

QC 20160524

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

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Karayiannidis, YiannisSmith, ChristianBarrientos, Francisco Eli VinaÖgren, PetterKragic, Danica
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