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Flexible Robot to Object Interactions Through Rigid and Deformable Cages
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.ORCID iD: 0000-0001-9362-0644
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis we study the problem of robotic interaction with objects from a flexible perspective that complements the rigid force-closure approach. In a flexible interaction the object is not firmly bound to the robot (immobilized), which leads to many interesting scenarios. We focus on the secure kind of flexible interactions, commonly referred to as caging grasps. In this context, the adjective secure implies that the object is not able to escape arbitrarily far away from the robot which is caging it. A cage is a secure flexible interaction because it does not immobilize the object, but restricts its motion to a finite set of possible configurations. We study cages in two novel scenarios for objects with holes: caging through multi-agent cooperation and through dual-arm knotting with a rope. From these two case studies, we were able to analyze the caging problem in a broader perspective leading to the definition of a hierarchical classification of flexible interactions and cages.

In parallel to the geometric and physical problem of flexible interactions with objects, we study also the problem of discrete action scheduling through a novel control architecture called Behavior Trees (BTs). In this thesis we propose a formulation that unifies the competing BT philosophies into a single framework. We analyze how the mainstream BT formulations differ from each other, as well as their benefits and limitations. We also compare the plan representation capabilities of BTs with respect to the traditional approach of Controlled Hybrid Dynamical Systems (CHDSs). In this regard, we present bidirectional translation algorithms between such representations as well as the necessary and sufficient conditions for translation convergence. Lastly, we demonstrate our action scheduling BT architecture showcasing the aforementioned caging scenarios, as well as other examples that show how BTs can be interfaced with other high level planners.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. , p. 145
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2017:08
Keywords [en]
planning, control, perception, caging, cage, grasping, multi-agent, robot, robotic, knot, knotting, behaviour trees, behavior trees, action scheduling, RRT
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-203994ISBN: 978-91-7729-316-3 (print)ISBN: 978-91-7729-316-3 (electronic)OAI: oai:DiVA.org:kth-203994DiVA, id: diva2:1083639
Public defence
2017-04-10, F3, Lindstedtsvägen 26, KTH Campus., Stockholm, 14:00 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, 600825
Note

QC 20170322

Available from: 2017-03-22 Created: 2017-03-21 Last updated: 2017-03-22Bibliographically approved
List of papers
1. Towards a Unified Behavior Trees Framework for Robot Control
Open this publication in new window or tab >>Towards a Unified Behavior Trees Framework for Robot Control
2014 (English)In: Robotics and Automation (ICRA), 2014 IEEE International Conference on , IEEE Robotics and Automation Society, 2014, p. 5420-5427Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a unified framework for Behavior Trees (BTs), a plan representation and execution tool. The available literature lacks the consistency and mathematical rigor required for robotic and control applications. Therefore, we approach this problem in two steps: first, reviewing the most popular BT literature exposing the aforementioned issues; second, describing our unified BT framework along with equivalence notions between BTs and Controlled Hybrid Dynamical Systems (CHDSs). This paper improves on the existing state of the art as it describes BTs in a more accurate and compact way, while providing insight about their actual representation capabilities. Lastly, we demonstrate the applicability of our framework to real systems scheduling open-loop actions in a grasping mission that involves a NAO robot and our BT library.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2014
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-165676 (URN)10.1109/ICRA.2014.6907656 (DOI)
Conference
IEEE International Conference on Robots and Automation,Hong Kong,May 31 2014-June 7 2014
Note

QC 20150507

Available from: 2015-04-29 Created: 2015-04-29 Last updated: 2018-01-11Bibliographically approved
2. Maximally Satisfying LTL Action Planning
Open this publication in new window or tab >>Maximally Satisfying LTL Action Planning
2014 (English)In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2014), IEEE , 2014, p. 1503-1510Conference paper, Published paper (Refereed)
Abstract [en]

We focus on autonomous robot action planning problem from Linear Temporal Logic (LTL) specifications, where the action refers to a "simple" motion or manipulation task, such as "go from A to B" or "grasp a ball". At the high-level planning layer, we propose an algorithm to synthesize a maximally satisfying discrete control strategy while taking into account that the robot's action executions may fail. Furthermore, we interface the high-level plan with the robot's low-level controller through a reactive middle-layer formalism called Behavior Trees (BTs). We demonstrate the proposed framework using a NAO robot capable of walking, ball grasping and ball dropping actions.

Place, publisher, year, edition, pages
IEEE, 2014
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Keywords
Intelligent robots, Robots, Temporal logic, Action execution, Action planning, Behavior trees, Discrete control strategies, Linear temporal logic specifications, Low-level controllers, Manipulation task, Robot actions
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-163507 (URN)10.1109/IROS.2014.6942755 (DOI)000349834601089 ()2-s2.0-84911499807 (Scopus ID)978-1-4799-6934-0 (ISBN)
Conference
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014, Palmer House Hilton Hotel Chicago, United States, 14 September 2014 through 18 September 2014
Note

QC 20150407

Available from: 2015-04-07 Created: 2015-04-07 Last updated: 2018-01-11Bibliographically approved
3. Cooperative grasping through topological object representation
Open this publication in new window or tab >>Cooperative grasping through topological object representation
2015 (English)In: IEEE-RAS International Conference on Humanoid Robots, IEEE Computer Society, 2015, p. 685-692Conference paper, Published paper (Refereed)
Abstract [en]

We present a cooperative grasping approach based on a topological representation of objects. Using point cloud data we extract loops on objects suitable for generating entanglement. We use the Gauss Linking Integral to derive controllers for multi-agent systems that generate hooking grasps on such loops while minimizing the entanglement between robots. The approach copes well with noisy point cloud data, it is computationally simple and robust. We demonstrate the method for performing object grasping and transportation, through a hooking maneuver, with two coordinated NAO robots.

Place, publisher, year, edition, pages
IEEE Computer Society, 2015
Keywords
Anthropomorphic robots, Robots, Topology, Noisy point, Object grasping, Point cloud data, Topological objects, Topological representation, Multi agent systems
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-181529 (URN)10.1109/HUMANOIDS.2014.7041437 (DOI)2-s2.0-84945179216 (Scopus ID)9781479971749 (ISBN)
Conference
2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014, 18 November 2014 through 20 November 2014
Note

QC 20160318

Available from: 2016-03-18 Created: 2016-02-02 Last updated: 2018-01-10Bibliographically approved
4. Rope through Loop Insertion for Robotic Knotting: A Virtual Magnetic Field Formulation
Open this publication in new window or tab >>Rope through Loop Insertion for Robotic Knotting: A Virtual Magnetic Field Formulation
2016 (English)Report (Other academic)
Abstract [en]

Inserting an end of a rope through a loop is a common and important action that is required for creating most types of knots. To perform this action, we need to pass the end of the rope through an area that is enclosed by another segment of rope. As for all knotting actions, the robot must for this exercise control over a semi-compliant and flexible body whose complex 3d shape is difficult to perceive and follow. Additionally, the target loop often deforms during the insertion. We address this problem by defining a virtual magnetic field through the loop's interior and use the Biot Savart law to guide the robotic manipulator that holds the end of the rope. This approach directly defines, for any manipulator position, a motion vector that results in a path that passes through the loop. The motion vector is directly derived from the position of the loop and changes as soon as it moves or deforms. In simulation, we test the insertion action against dynamic loop deformation of different intensity. We also combine insertion with grasp and release actions, coordinated by a hybrid control system, to tie knots in simulation and with a NAO robot.

Place, publisher, year, edition, pages
Stockholm: , 2016. p. 8
Keywords
robotics, dual-arm, control, knotting, automation
National Category
Robotics
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-196952 (URN)978-91-7729-218-0 (ISBN)
Note

QC 20170110

Available from: 2016-11-27 Created: 2016-11-27 Last updated: 2017-03-22Bibliographically approved

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