Optimization-based human-in-the-loop manipulation using joint space polytopes

Philip Long; Tarik Kelestemur; Aykut Ozgun Onol; Taskin Padir

doi:10.1109/ICRA.2019.8794071

Optimization-based human-in-the-loop manipulation using joint space polytopes

Philip Long, Tarik Kelestemur, Aykut Ozgun Onol, Taskin Padir

Northeastern University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

This paper presents a new method of maximizing the free space for a robot operating in a constrained environment under operator supervision. The objective is to make the resulting trajectories more robust to operator commands and/or changes in the environment. To represent the volume of free space, the constrained manipulability polytopes are used. These polytopes embed the distance to obstacles, the distance to joint limits and the distance to singular configurations. The volume of the resulting Cartesian polyhedron is used in an optimization-based motion planner to create the trajectories. Additionally, we show how fast collision-free inverse kinematic solutions can be obtained by exploiting the pre-computed inequality constraints. The proposed algorithm is validated in simulation and experimentally.

Original language	English
Title of host publication	2019 International Conference on Robotics and Automation, ICRA 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	204-210
Number of pages	7
ISBN (Electronic)	9781538660263
DOIs	https://doi.org/10.1109/ICRA.2019.8794071
Publication status	Published - May 2019
Externally published	Yes
Event	2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada Duration: 20 May 2019 → 24 May 2019

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2019-May
ISSN (Print)	1050-4729

Conference

Conference	2019 International Conference on Robotics and Automation, ICRA 2019
Country/Territory	Canada
City	Montreal
Period	20/05/19 → 24/05/19

Access to Document

10.1109/ICRA.2019.8794071

Cite this

Long, P., Kelestemur, T., Onol, A. O., & Padir, T. (2019). Optimization-based human-in-the-loop manipulation using joint space polytopes. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 204-210). Article 8794071 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2019.8794071

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title = "Optimization-based human-in-the-loop manipulation using joint space polytopes",

abstract = "This paper presents a new method of maximizing the free space for a robot operating in a constrained environment under operator supervision. The objective is to make the resulting trajectories more robust to operator commands and/or changes in the environment. To represent the volume of free space, the constrained manipulability polytopes are used. These polytopes embed the distance to obstacles, the distance to joint limits and the distance to singular configurations. The volume of the resulting Cartesian polyhedron is used in an optimization-based motion planner to create the trajectories. Additionally, we show how fast collision-free inverse kinematic solutions can be obtained by exploiting the pre-computed inequality constraints. The proposed algorithm is validated in simulation and experimentally.",

author = "Philip Long and Tarik Kelestemur and Onol, {Aykut Ozgun} and Taskin Padir",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Conference on Robotics and Automation, ICRA 2019 ; Conference date: 20-05-2019 Through 24-05-2019",

year = "2019",

month = may,

doi = "10.1109/ICRA.2019.8794071",

language = "English",

series = "Proceedings - IEEE International Conference on Robotics and Automation",

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Long, P, Kelestemur, T, Onol, AO & Padir, T 2019, Optimization-based human-in-the-loop manipulation using joint space polytopes. in 2019 International Conference on Robotics and Automation, ICRA 2019., 8794071, Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., pp. 204-210, 2019 International Conference on Robotics and Automation, ICRA 2019, Montreal, Canada, 20/05/19. https://doi.org/10.1109/ICRA.2019.8794071

Optimization-based human-in-the-loop manipulation using joint space polytopes. / Long, Philip; Kelestemur, Tarik; Onol, Aykut Ozgun et al.
2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 204-210 8794071 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents a new method of maximizing the free space for a robot operating in a constrained environment under operator supervision. The objective is to make the resulting trajectories more robust to operator commands and/or changes in the environment. To represent the volume of free space, the constrained manipulability polytopes are used. These polytopes embed the distance to obstacles, the distance to joint limits and the distance to singular configurations. The volume of the resulting Cartesian polyhedron is used in an optimization-based motion planner to create the trajectories. Additionally, we show how fast collision-free inverse kinematic solutions can be obtained by exploiting the pre-computed inequality constraints. The proposed algorithm is validated in simulation and experimentally.

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M3 - Conference contribution

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Long P, Kelestemur T, Onol AO, Padir T. Optimization-based human-in-the-loop manipulation using joint space polytopes. In 2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 204-210. 8794071. (Proceedings - IEEE International Conference on Robotics and Automation). doi: 10.1109/ICRA.2019.8794071

Optimization-based human-in-the-loop manipulation using joint space polytopes

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