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Iliev, Boyko
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Publications (10 of 37) Show all publications
Palm, R. & Iliev, B. (2014). Programming-by-Demonstration and Adaptation of Robot Skills by Fuzzy Time Modeling. International Journal of Humanoid Robotics, 11(1), Article ID 1450009.
Open this publication in new window or tab >>Programming-by-Demonstration and Adaptation of Robot Skills by Fuzzy Time Modeling
2014 (English)In: International Journal of Humanoid Robotics, ISSN 0219-8436, Vol. 11, no 1, article id 1450009Article in journal (Refereed) Published
Abstract [en]

Robot skills are motion or grasping primitives from which a complicated robot task consists. Skills can be directly learned and recognized by a technique named programming-bydemonstration. A human operator demonstrates a set of reference skills where his motions are recorded by a data-capturing system and modeled via fuzzy clustering and a Takagi–Sugeno modeling technique. The skill models use time instants as input and operator actions as outputs. In the recognition phase, the robot identi¯es the skill shown by the operator in a novel test demonstration. Finally, using the corresponding reference skill model the robot executes the recognized skill. Skill models can be updated online where drastic di®erences between learned and real world conditions are eliminated using the Broyden update formula. This method was extended for fuzzy models especially for time cluster models.

Place, publisher, year, edition, pages
Singapore: World Scientific, 2014
Keywords
Fuzzy modeling; time clustering; robot skills; programming-by-demonstration
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-34713 (URN)10.1142/S0219843614500091 (DOI)000334602700007 ()2-s2.0-84898453229 (Scopus ID)
Note

Funding Agencies:

HANDLE project

European Communitys Seventh Framework Programme

Available from: 2014-04-12 Created: 2014-04-12 Last updated: 2017-10-18Bibliographically approved
Charusta, K., Krug, R., Stoyanov, T., Dimitrov, D. & Iliev, B. (2012). Generation of independent contact regions on objects reconstructed from noisy real-world range data. In: 2012 IEEE International Conference on Robotics and Automation (ICRA): . Paper presented at 2012 IEEE International Conference on Robotics and Automation (ICRA), St Paul, MN, USA, May 14-18, 2012 (pp. 1338-1344). IEEE conference proceedings
Open this publication in new window or tab >>Generation of independent contact regions on objects reconstructed from noisy real-world range data
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2012 (English)In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2012, p. 1338-1344Conference paper, Published paper (Refereed)
Abstract [en]

The synthesis and evaluation of multi-fingered grasps on complex objects is a challenging problem that has received much attention in the robotics community. Although several promising approaches have been developed, applications to real-world systems are limited to simple objects or gripper configurations. The paradigm of Independent Contact Regions (ICRs) has been proposed as a way to increase the tolerance to grasp positioning errors. This concept is well established, though only on precise geometric object models. This work is concerned with the application of the ICR paradigm to models reconstructed from real-world range data. We propose a method for increasing the robustness of grasp synthesis on uncertain geometric models. The sensitivity of the ICR algorithm to noisy data is evaluated and a filtering approach is proposed to improve the quality of the final result.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012
Series
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keywords
cameras, image reconstruction, manipulators, prototypes, robot sensing systems, dexterous manipulators, filtering theory, grippers, image reconstruction
National Category
Robotics Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-24192 (URN)10.1109/ICRA.2012.6225046 (DOI)000309406701053 ()2-s2.0-84864455775 (Scopus ID)9781467314053 (ISBN)9781467314039 (ISBN)
Conference
2012 IEEE International Conference on Robotics and Automation (ICRA), St Paul, MN, USA, May 14-18, 2012
Funder
EU, FP7, Seventh Framework Programme
Available from: 2012-08-06 Created: 2012-08-01 Last updated: 2018-01-12Bibliographically approved
Charusta, K., Krug, R., Dimitrov, D. & Iliev, B. (2012). Independent contact regions based on a patch contact model. In: 2012 IEEE International Conference on Robotics and Automation (ICRA): . Paper presented at 2012 IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, MN, USA, May 14-18, 2012 (pp. 4162-4169). IEEE conference proceedings
Open this publication in new window or tab >>Independent contact regions based on a patch contact model
2012 (English)In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2012, p. 4162-4169Conference paper, Published paper (Refereed)
Abstract [en]

The synthesis of multi-fingered grasps on nontrivial objects requires a realistic representation of the contact between the fingers of a robotic hand and an object. In this work, we use a patch contact model to approximate the contact between a rigid object and a deformable anthropomorphic finger. This contact model is utilized in the computation of Independent Contact Regions (ICRs) that have been proposed as a way to compensate for shortcomings in the finger positioning accuracy of robotic grasping devices. We extend the ICR algorithm to account for the patch contact model and show the benefits of this solution.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012
Series
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keywords
computational modeling, force, geometry, grasping, humans, robots, dexterous manipulators, mechanical contact, position control
National Category
Robotics Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-24193 (URN)10.1109/ICRA.2012.6225325 (DOI)000309406704028 ()2-s2.0-84864429733 (Scopus ID)978-1-4673-1405-3 (ISBN)978-1-4673-1403-9 (ISBN)
Conference
2012 IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, MN, USA, May 14-18, 2012
Funder
EU, FP7, Seventh Framework Programme
Available from: 2012-08-06 Created: 2012-08-01 Last updated: 2018-01-12Bibliographically approved
Berglund, E., Iliev, B., Palm, R., Krug, R., Charusta, K. & Dimitrov, D. (2012). Mapping between different kinematic structures without absolute positioning during operation [Letter to the editor]. Electronics Letters, 48(18), 1110-1112
Open this publication in new window or tab >>Mapping between different kinematic structures without absolute positioning during operation
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2012 (English)In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 48, no 18, p. 1110-1112Article in journal, Letter (Refereed) Published
Abstract [en]

When creating datasets for modelling of human skills based on training examples from human motion, one can encounter the problem that the kinematics of the robot does not match the human kinematics. Presented is a simple method of bypassing the explicit modelling of the human kinematics based on a variant of the self-organising map (SOM) algorithm. While the literature contains instances of SOM-type algorithms used for dimension reduction, this reported work deals with the inverse problem: dimension increase, as we are going from 4 to 5 degrees of freedom.

Keywords
robot kinematics, self-organising feature maps, SOM-type algorithms, human kinematics, human motion, human skills modelling, kinematic structures, robot kinematics, self-organising map algorithm, training examples
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-28853 (URN)10.1049/el.2012.1085 (DOI)000308552200016 ()
Note

Research funder: European Union, HANDLE project (no project number available)

Available from: 2013-04-29 Created: 2013-04-29 Last updated: 2018-01-11Bibliographically approved
Krug, R., Dimitrov, D., Charusta, K. & Iliev, B. (2011). Prioritized independent contact regions for form closure grasps. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: . Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems SEP 25-30, 2011 San Francisco, CA, USA (pp. 1797-1803).
Open this publication in new window or tab >>Prioritized independent contact regions for form closure grasps
2011 (English)In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011, p. 1797-1803Conference paper, Published paper (Refereed)
Abstract [en]

The concept of independent contact regions on a target object's surface, in order to compensate for shortcomings in the positioning accuracy of robotic grasping devices, is well known. However, the numbers and distributions of contact points forming such regions is not unique and depends on the underlying computational method. In this work we present a computation scheme allowing to prioritize contact points for inclusion in the independent regions. This enables a user to affect their shape in order to meet the demands of the targeted application. The introduced method utilizes frictionless contact constraints and is able to efficiently approximate the space of disturbances resistible by all grasps comprising contacts within the independent regions.

Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Keywords
Contact points; Contact regions; Form closure; Frictionless contacts; Positioning accuracy; Robotic grasping; Target object
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-22333 (URN)10.1109/IROS.2011.6094653 (DOI)000297477502023 ()2-s2.0-84455200614 (Scopus ID)978-1-61284-455-8 (ISBN)9781612844541 (ISBN)
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems SEP 25-30, 2011 San Francisco, CA, USA
Available from: 2012-04-02 Created: 2012-04-02 Last updated: 2018-01-12Bibliographically approved
Palm, R., Iliev, B. & Kadmiry, B. (2010). Grasp recognition by fuzzy modeling and hidden Markov models. In: Honghai Liu, Dongbing Gu, Robert J. Howlett, Yonghuai Liu (Ed.), Robot intelligence: an advanced knowledge processing approach (pp. 25-47). New York: Springer
Open this publication in new window or tab >>Grasp recognition by fuzzy modeling and hidden Markov models
2010 (English)In: Robot intelligence: an advanced knowledge processing approach / [ed] Honghai Liu, Dongbing Gu, Robert J. Howlett, Yonghuai Liu, New York: Springer , 2010, p. 25-47Chapter in book (Other academic)
Abstract [en]

Grasp recognition is a major part of the approach for Programming-by-Demonstration (PbD) for five-fingered robotic hands. This chapter describes three different methods for grasp recognition for a human hand. A human operator wearing a data glove instructs the robot to perform different grasps. For a number of human grasps the finger joint angle trajectories are recorded and modeled by fuzzy clustering and Takagi-Sugeno modeling. This leads to grasp models using time as input parameter and joint angles as outputs. Given a test grasp by the human operator the robot classifies and recognizes the grasp and generates the corresponding robot grasp. Three methods for grasp recognition are compared with each other. In the first method, the test grasp is compared with model grasps using the difference between the model outputs. The second method deals with qualitative fuzzy models which used for recognition and classification. The third method is based on Hidden-Markov-Models (HMM) which are commonly used in robot learning.

Place, publisher, year, edition, pages
New York: Springer, 2010
National Category
Control Engineering
Research subject
Automatic Control
Identifiers
urn:nbn:se:oru:diva-14336 (URN)10.1007/978-1-84996-329-9_2 (DOI)978-1-84996-328-2 (ISBN)
Available from: 2011-01-27 Created: 2011-01-27 Last updated: 2017-10-18Bibliographically approved
Palm, R. & Iliev, B. (2010). Learning and adaptation of robot skills using fuzzy models. In: 2010 IEEE International Conference on Fuzzy Systems (FUZZ): . Paper presented at 2010 IEEE International Conference on Fuzzy Systems (FUZZ), Barcelona, 18-23 July (pp. 1-8). IEEE conference proceedings
Open this publication in new window or tab >>Learning and adaptation of robot skills using fuzzy models
2010 (English)In: 2010 IEEE International Conference on Fuzzy Systems (FUZZ), IEEE conference proceedings, 2010, p. 1-8Conference paper, Published paper (Other academic)
Abstract [en]

Robot skills can be taught and recognized by a Programming-by-Demonstration technique where first a human operator demonstrates a set of reference skills. The operator's motions are then recorded by a data-capturing system and modeled via fuzzy clustering and a Takagi-Sugeno modeling technique. The resulting skill models use the time as input and the operator's actions as outputs. During the recognition phase, the robot recognizes which skill has been used by the operator in a novel demonstration. This is done by comparison between the time clusters of the test skill and those of the reference skills. Finally, the robot executes the recognized skill by using the corresponding reference skill model. Drastic differences between learned and real world conditions which occur during the execution of skills by the robot are eliminated by using the Broyden update formula for Jacobians. This method was extended for fuzzy models especially for time cluster models. After the online training of a skill model the updated model is used for further executions of the same skill by the robot.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
National Category
Engineering and Technology
Research subject
Automatic Control
Identifiers
urn:nbn:se:oru:diva-19090 (URN)10.1109/FUZZY.2010.5584536 (DOI)000287453600037 ()978-1-4244-6919-2 (ISBN)
Conference
2010 IEEE International Conference on Fuzzy Systems (FUZZ), Barcelona, 18-23 July
Available from: 2011-10-03 Created: 2011-09-30 Last updated: 2018-02-07Bibliographically approved
Krug, R., Dimitrov, D., Charusta, K. & Iliev, B. (2010). On the efficient computation of independent contact regions for force closure grasps. In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010): . Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, Oct 18-22, 2010 (pp. 586-591). IEEE conference proceedings
Open this publication in new window or tab >>On the efficient computation of independent contact regions for force closure grasps
2010 (English)In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010), IEEE conference proceedings, 2010, p. 586-591Conference paper, Published paper (Other academic)
Abstract [en]

Since the introduction of independent contact regions in order to compensate for shortcomings in the positioning accuracy of robotic hands, alternative methods for their generation have been proposed. Due to the fact that (in general) such regions are not unique, the computation methods used usually reflect the envisioned application and/or underlying assumptions made. This paper introduces a parallelizable algorithm for the efficient computation of independent contact regions, under the assumption that a user input in the form of initial guess for the grasping points is readily available. The proposed approach works on discretized 3D-objects with any number of contacts and can be used with any of the following models: frictionless point contact, point contact with friction and soft finger contact. An example of the computation of independent contact regions comprising a non-trivial task wrench space is given.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-19085 (URN)10.1109/IROS.2010.5654380 (DOI)000287672005063 ()978-1-4244-6675-7 (ISBN)
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, Oct 18-22, 2010
Available from: 2011-10-03 Created: 2011-09-30 Last updated: 2018-01-12Bibliographically approved
Skoglund, A., Iliev, B. & Palm, R. (2010). Programming-by-demonstration of reaching motions: a next-state-planner approach. Robotics and Autonomous Systems, 58(5), 607-621
Open this publication in new window or tab >>Programming-by-demonstration of reaching motions: a next-state-planner approach
2010 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 58, no 5, p. 607-621Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel approach to skill acquisition from human demonstration. A robot manipulator with a morphology which is very different from the human arm simply cannot copy a human motion, but has to execute its own version of the skill. When a skill once has been acquired the robot must also be able to generalize to other similar skills, without a new learning process. By using a motion planner that operates in an object-related world frame called hand-state, we show that this representation simplifies skill reconstruction and preserves the essential parts of the skill. (C) 2010 Elsevier B.V. All rights reserved.

Keywords
Programming-by-Demonstration, Hand-state, Motion planner, Fuzzy modeling, Correspondence problem
National Category
Control Engineering
Research subject
Automatic Control
Identifiers
urn:nbn:se:oru:diva-12948 (URN)10.1016/j.robot.2009.12.003 (DOI)000277926200017 ()
Available from: 2011-01-04 Created: 2011-01-03 Last updated: 2018-04-23Bibliographically approved
Skoglund, A., Iliev, B. & Palm, R. (2010). Programming-by-demonstration of reaching motions using a next-state-planner. In: Ernest Hall (Ed.), Advances in robot manipulators (pp. 479-501). Rijeka, Croatia: InTech
Open this publication in new window or tab >>Programming-by-demonstration of reaching motions using a next-state-planner
2010 (English)In: Advances in robot manipulators / [ed] Ernest Hall, Rijeka, Croatia: InTech , 2010, p. 479-501Chapter in book (Other academic)
Place, publisher, year, edition, pages
Rijeka, Croatia: InTech, 2010
Keywords
robotics, robot manipulators
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-14324 (URN)978-953-307-070-4 (ISBN)
Available from: 2011-01-26 Created: 2011-01-26 Last updated: 2018-01-12Bibliographically approved
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