Model-based tracking of miniaturized grippers using particle swarm optimization

Stefano Scheggi, ChangKyu Yoon, David H. Gracias, Sarthak Misra

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
54 Downloads (Pure)

Abstract

Micro-sized agents can benefit robotic minimally invasive surgery since they can be inserted into the human body and use natural pathways such as arteries and veins or the gastrointestinal tract, to reach their target for drug delivery or diagnosis. Recently, miniaturized agents with shape-changing and gripping capabilities have provided significant advantages in performing grasping, transportation, and manipulation tasks. In order to robustly perform such tasks, it is of utmost importance to properly estimate their overall configuration. This paper presents a novel solution to the problem of estimating and tracking the 3D position, orientation and configuration of the tips of miniaturized grippers from RGB marker-less visual observations obtained by a microscope. We consider this as an optimization problem, seeking for the gripper model parameters that minimize the discrepancy between hypothesized instances of the gripper model and actual observations of the miniaturized gripper. This optimization problem is solved using a variant of the Particle Swarm Optimization algorithm. The proposed approach has been evaluated on several image sequences showing the grippers moving, rotating, opening/closing and grasping biological material.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016)
Place of PublicationDaejeon, Korea
PublisherIEEE
Pages454-459
DOIs
Publication statusPublished - 9 Oct 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon Convention Center, Daejeon, Korea, Republic of
Duration: 9 Oct 201614 Oct 2016
http://www.iros2016.org/

Publication series

Name
PublisherIEEE
ISSN (Print)2153-0866
ISSN (Electronic)2153-0866

Conference

Conference2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Abbreviated titleIROS
CountryKorea, Republic of
CityDaejeon
Period9/10/1614/10/16
Internet address

Fingerprint

Grippers
Particle swarm optimization (PSO)
Drug delivery
Biological materials
Surgery
Robotics
Microscopes

Keywords

  • METIS-318183
  • IR-101642

Cite this

Scheggi, S., Yoon, C., Gracias, D. H., & Misra, S. (2016). Model-based tracking of miniaturized grippers using particle swarm optimization. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016) (pp. 454-459). Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759093
Scheggi, Stefano ; Yoon, ChangKyu ; Gracias, David H. ; Misra, Sarthak. / Model-based tracking of miniaturized grippers using particle swarm optimization. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016). Daejeon, Korea : IEEE, 2016. pp. 454-459
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title = "Model-based tracking of miniaturized grippers using particle swarm optimization",
abstract = "Micro-sized agents can benefit robotic minimally invasive surgery since they can be inserted into the human body and use natural pathways such as arteries and veins or the gastrointestinal tract, to reach their target for drug delivery or diagnosis. Recently, miniaturized agents with shape-changing and gripping capabilities have provided significant advantages in performing grasping, transportation, and manipulation tasks. In order to robustly perform such tasks, it is of utmost importance to properly estimate their overall configuration. This paper presents a novel solution to the problem of estimating and tracking the 3D position, orientation and configuration of the tips of miniaturized grippers from RGB marker-less visual observations obtained by a microscope. We consider this as an optimization problem, seeking for the gripper model parameters that minimize the discrepancy between hypothesized instances of the gripper model and actual observations of the miniaturized gripper. This optimization problem is solved using a variant of the Particle Swarm Optimization algorithm. The proposed approach has been evaluated on several image sequences showing the grippers moving, rotating, opening/closing and grasping biological material.",
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Scheggi, S, Yoon, C, Gracias, DH & Misra, S 2016, Model-based tracking of miniaturized grippers using particle swarm optimization. in Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016). IEEE, Daejeon, Korea, pp. 454-459, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016, Daejeon, Korea, Republic of, 9/10/16. https://doi.org/10.1109/IROS.2016.7759093

Model-based tracking of miniaturized grippers using particle swarm optimization. / Scheggi, Stefano; Yoon, ChangKyu; Gracias, David H.; Misra, Sarthak.

Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016). Daejeon, Korea : IEEE, 2016. p. 454-459.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Model-based tracking of miniaturized grippers using particle swarm optimization

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N2 - Micro-sized agents can benefit robotic minimally invasive surgery since they can be inserted into the human body and use natural pathways such as arteries and veins or the gastrointestinal tract, to reach their target for drug delivery or diagnosis. Recently, miniaturized agents with shape-changing and gripping capabilities have provided significant advantages in performing grasping, transportation, and manipulation tasks. In order to robustly perform such tasks, it is of utmost importance to properly estimate their overall configuration. This paper presents a novel solution to the problem of estimating and tracking the 3D position, orientation and configuration of the tips of miniaturized grippers from RGB marker-less visual observations obtained by a microscope. We consider this as an optimization problem, seeking for the gripper model parameters that minimize the discrepancy between hypothesized instances of the gripper model and actual observations of the miniaturized gripper. This optimization problem is solved using a variant of the Particle Swarm Optimization algorithm. The proposed approach has been evaluated on several image sequences showing the grippers moving, rotating, opening/closing and grasping biological material.

AB - Micro-sized agents can benefit robotic minimally invasive surgery since they can be inserted into the human body and use natural pathways such as arteries and veins or the gastrointestinal tract, to reach their target for drug delivery or diagnosis. Recently, miniaturized agents with shape-changing and gripping capabilities have provided significant advantages in performing grasping, transportation, and manipulation tasks. In order to robustly perform such tasks, it is of utmost importance to properly estimate their overall configuration. This paper presents a novel solution to the problem of estimating and tracking the 3D position, orientation and configuration of the tips of miniaturized grippers from RGB marker-less visual observations obtained by a microscope. We consider this as an optimization problem, seeking for the gripper model parameters that minimize the discrepancy between hypothesized instances of the gripper model and actual observations of the miniaturized gripper. This optimization problem is solved using a variant of the Particle Swarm Optimization algorithm. The proposed approach has been evaluated on several image sequences showing the grippers moving, rotating, opening/closing and grasping biological material.

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Scheggi S, Yoon C, Gracias DH, Misra S. Model-based tracking of miniaturized grippers using particle swarm optimization. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016). Daejeon, Korea: IEEE. 2016. p. 454-459 https://doi.org/10.1109/IROS.2016.7759093