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Cooperative Manipulation and Identification of a 2-DOF Articulated Object by a Dual-Arm Robot
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. (RPL)ORCID iD: 0000-0003-3252-715X
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. Dept. of Electrical Eng., Chalmers University of Technology.ORCID iD: 0000-0001-5129-342X
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) / [ed] IEEE, 2018, p. 5445-5451Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we address the dual-arm manipula-tion of a two degrees-of-freedom articulated object that consistsof two rigid links. This can include a linkage constrainedalong two motion directions, or two objects in contact, wherethe contact imposes motion constraints. We formulate theproblem as a cooperative task, which allows the employment ofcoordinated task space frameworks, thus enabling redundancyexploitation by adjusting how the task is shared by the robotarms. In addition, we propose a method that can estimate thejoint location and the direction of the degrees-of-freedom, basedon the contact forces and the motion constraints imposed bythe object. Experimental results demonstrate the performanceof the system in its ability to estimate the two degrees of freedomindependently or simultaneously.

Place, publisher, year, edition, pages
2018. p. 5445-5451
Keywords [en]
Robotics, Dual-Arm, Manipulation, Estimation, Adaptive, Filtering
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-226562DOI: 10.1109/ICRA.2018.8460511ISI: 000446394504016Scopus ID: 2-s2.0-85063142273ISBN: 978-1-5386-3081-5 (print)OAI: oai:DiVA.org:kth-226562DiVA, id: diva2:1199313
Conference
IEEE International Conference on Robotics and Automation (ICRA), 2018
Projects
SARAFun
Note

QC 20180423

Available from: 2018-04-20 Created: 2018-04-20 Last updated: 2020-03-05Bibliographically approved
In thesis
1. Dual-Arm Robotic Manipulation under Uncertainties and Task-Based Redundancy
Open this publication in new window or tab >>Dual-Arm Robotic Manipulation under Uncertainties and Task-Based Redundancy
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Robotic manipulators are mostly employed in industrial environments, where their tasks can be prescribed with little to no uncertainty. This is possible in scenarios where the deployment time of robot workcells is not prohibitive, such as in the automotive industry. In other contexts, however, the time cost of setting up a classical robotic automation workcell is often prohibitive. This is the case with cellphone manufacturing, for example, which is currently mostly executed by human workers. Robotic automation is nevertheless desirable in these human-centric environments, as a robot can automate the most tedious parts of an assembly. To deploy robots in these environments, however, requires an ability to deal with uncertainties and to robustly execute any given task. In this thesis, we discuss two topics related to autonomous robotic manipulation. First, we address parametric uncertainties in manipulation tasks, such as the location of contacts during the execution of an assembly. We propose and experimentally evaluate two methods that rely on force and torque measurements to produce estimates of task related uncertainties: a method for dexterous manipulation under uncertainties which relies on a compliant rotational degree of freedom at the robot's gripper grasp point and exploits contact  with an external surface, and a cooperative manipulation system which is able to identify the kinematics of a two degrees of freedom mechanism. Then, we consider redundancies in dual-arm robotic manipulation. Dual-armed robots offer a large degree of redundancy which can be exploited to ensure a more robust task execution. When executing an assembly task, for instance, robots can freely change the location of the assembly in their workspace without affecting the task execution. We discuss methods that explore these types of redundancies in relative motion tasks in the form of asymmetries in their execution. Finally, we approach the converse problem by presenting a system which is able to balance measured forces and torques at its end-effectors by leveraging relative motion between them, while grasping a rigid tray. This is achieved through discrete sliding of the grasp points, which constitutes a novel application of bimanual dexterous manipulation.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019. p. 40
Series
TRITA-EECS-AVL ; 2019:73
National Category
Robotics
Identifiers
urn:nbn:se:kth:diva-263043 (URN)978-91-7873-331-6 (ISBN)
Public defence
2019-11-22, Room F3, Lindstedtsvägen 26, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20191105

Available from: 2019-11-05 Created: 2019-10-28 Last updated: 2019-11-18Bibliographically approved

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Almeida, DiogoKarayiannidis, Yiannis

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