Collision detection of humanoid robot arm under model uncertainties for handling of unknown object

Sang Duck Lee; Jae-Bok Song

doi:10.1109/HUMANOIDS.2015.7363433

Collision detection of humanoid robot arm under model uncertainties for handling of unknown object

Sang Duck Lee, Jae-Bok Song

Department of Mechanical Engineering

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

3 Citations (Scopus)

Abstract

In recent years human-robot collision safety has received considerable attention. Thus, various collision detection algorithms have been proposed to ensure human-robot collision safety, and these algorithms are usually model-based. However, the dynamic model of a robot arm is uncertain or unknown in cases where the arm performs a task with various objects or tools. In this paper, we propose a collision detection method for a robot arm that changes its tools or pick up various objects. For this purpose, a novel collision detection index, which is decoupled from the inevitable external force generated by the object being handled by the robot, is developed. The proposed index is verified through various simulations using a 7-DOF robot arm, and the corresponding results show that regardless of the object that is being handled, it is possible to detect collisions.

Original language	English
Title of host publication	IEEE-RAS International Conference on Humanoid Robots
Publisher	IEEE Computer Society
Pages	718-721
Number of pages	4
Volume	2015-December
ISBN (Print)	9781479968855
DOIs	https://doi.org/10.1109/HUMANOIDS.2015.7363433
Publication status	Published - 2015 Dec 22
Event	15th IEEE RAS International Conference on Humanoid Robots, Humanoids 2015 - Seoul, Korea, Republic of Duration: 2015 Nov 3 → 2015 Nov 5

Other

Other	15th IEEE RAS International Conference on Humanoid Robots, Humanoids 2015
Country	Korea, Republic of
City	Seoul
Period	15/11/3 → 15/11/5

Keywords

Adaptation models
Collision avoidance
Force
Indexes
Mathematical model
Robots
Torque

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Hardware and Architecture
Human-Computer Interaction
Electrical and Electronic Engineering

Access to Document

10.1109/HUMANOIDS.2015.7363433

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Cite this

Lee, SD & Song, J-B 2015, Collision detection of humanoid robot arm under model uncertainties for handling of unknown object. in IEEE-RAS International Conference on Humanoid Robots. vol. 2015-December, 7363433, IEEE Computer Society, pp. 718-721, 15th IEEE RAS International Conference on Humanoid Robots, Humanoids 2015, Seoul, Korea, Republic of, 15/11/3. https://doi.org/10.1109/HUMANOIDS.2015.7363433

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title = "Collision detection of humanoid robot arm under model uncertainties for handling of unknown object",

abstract = "In recent years human-robot collision safety has received considerable attention. Thus, various collision detection algorithms have been proposed to ensure human-robot collision safety, and these algorithms are usually model-based. However, the dynamic model of a robot arm is uncertain or unknown in cases where the arm performs a task with various objects or tools. In this paper, we propose a collision detection method for a robot arm that changes its tools or pick up various objects. For this purpose, a novel collision detection index, which is decoupled from the inevitable external force generated by the object being handled by the robot, is developed. The proposed index is verified through various simulations using a 7-DOF robot arm, and the corresponding results show that regardless of the object that is being handled, it is possible to detect collisions.",

keywords = "Adaptation models, Collision avoidance, Force, Indexes, Mathematical model, Robots, Torque",

author = "Lee, {Sang Duck} and Jae-Bok Song",

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note = "15th IEEE RAS International Conference on Humanoid Robots, Humanoids 2015 ; Conference date: 03-11-2015 Through 05-11-2015",

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AU - Song, Jae-Bok

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N2 - In recent years human-robot collision safety has received considerable attention. Thus, various collision detection algorithms have been proposed to ensure human-robot collision safety, and these algorithms are usually model-based. However, the dynamic model of a robot arm is uncertain or unknown in cases where the arm performs a task with various objects or tools. In this paper, we propose a collision detection method for a robot arm that changes its tools or pick up various objects. For this purpose, a novel collision detection index, which is decoupled from the inevitable external force generated by the object being handled by the robot, is developed. The proposed index is verified through various simulations using a 7-DOF robot arm, and the corresponding results show that regardless of the object that is being handled, it is possible to detect collisions.

AB - In recent years human-robot collision safety has received considerable attention. Thus, various collision detection algorithms have been proposed to ensure human-robot collision safety, and these algorithms are usually model-based. However, the dynamic model of a robot arm is uncertain or unknown in cases where the arm performs a task with various objects or tools. In this paper, we propose a collision detection method for a robot arm that changes its tools or pick up various objects. For this purpose, a novel collision detection index, which is decoupled from the inevitable external force generated by the object being handled by the robot, is developed. The proposed index is verified through various simulations using a 7-DOF robot arm, and the corresponding results show that regardless of the object that is being handled, it is possible to detect collisions.

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KW - Mathematical model

KW - Robots

KW - Torque

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