Rule-Based Approach for Constrained Motion Control of a Teleoperated Robot Arm in a Dynamic Environment

Marie Claire Capolei*, Haiyan Wu, Adrian Llopart Maurin, Silvia Tolu, Ole Ravn

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This paper presents a preliminary robotic solution for constrained teleoperation tasks in an uncertain and dynamic environment. The robotic system is supported
by a reasoning agent which makes the control action reactive and context-sensitive. The investigation is motivated by the future Human-Robot collaboration, therefore, it focuses on minimizing or avoiding collisions within the robot and the surroundings objects. The report describes the developed control architecture, which, in its modular and hierarchical structure, combines knowledge from different areas such as control theory, path and trajectory planning, computer vision, collision avoidance, and decision-making theory. The software is implemented in a ROS framework, in order to support a clear and modular design, suitable for future extensions and integration on different hardware components. The experiments are run on both real and simulated systems. The results show an autonomous robot capable of continuously adapting its movements despite the external agent interruptions, with a 99% success rate. We can conclude that an adaptive robotic system capable of performing constrained tasks and simultaneously reacting to external stimuli in an uncertain and dynamic environment is potentially obtainable.
Original languageEnglish
JournalInternational Journal of Mechanical Engineering and Robotics Research
Volume8
Issue number3
Pages (from-to)393-400
ISSN2278-0149
DOIs
Publication statusPublished - 2019

Keywords

  • Rule-Based System
  • Decision-Making
  • Autonomous Robot
  • Intelligent system
  • Robot Control
  • Constrained Motion Control
  • ROS

Cite this

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title = "Rule-Based Approach for Constrained Motion Control of a Teleoperated Robot Arm in a Dynamic Environment",
abstract = "This paper presents a preliminary robotic solution for constrained teleoperation tasks in an uncertain and dynamic environment. The robotic system is supportedby a reasoning agent which makes the control action reactive and context-sensitive. The investigation is motivated by the future Human-Robot collaboration, therefore, it focuses on minimizing or avoiding collisions within the robot and the surroundings objects. The report describes the developed control architecture, which, in its modular and hierarchical structure, combines knowledge from different areas such as control theory, path and trajectory planning, computer vision, collision avoidance, and decision-making theory. The software is implemented in a ROS framework, in order to support a clear and modular design, suitable for future extensions and integration on different hardware components. The experiments are run on both real and simulated systems. The results show an autonomous robot capable of continuously adapting its movements despite the external agent interruptions, with a 99{\%} success rate. We can conclude that an adaptive robotic system capable of performing constrained tasks and simultaneously reacting to external stimuli in an uncertain and dynamic environment is potentially obtainable.",
keywords = "Rule-Based System, Decision-Making, Autonomous Robot, Intelligent system, Robot Control, Constrained Motion Control, ROS",
author = "Capolei, {Marie Claire} and Haiyan Wu and Maurin, {Adrian Llopart} and Silvia Tolu and Ole Ravn",
year = "2019",
doi = "10.18178/ijmerr.8.3.393-400",
language = "English",
volume = "8",
pages = "393--400",
journal = "International Journal of Mechanical Engineering and Robotics Research",
issn = "2278-0149",
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T1 - Rule-Based Approach for Constrained Motion Control of a Teleoperated Robot Arm in a Dynamic Environment

AU - Capolei, Marie Claire

AU - Wu, Haiyan

AU - Maurin, Adrian Llopart

AU - Tolu, Silvia

AU - Ravn, Ole

PY - 2019

Y1 - 2019

N2 - This paper presents a preliminary robotic solution for constrained teleoperation tasks in an uncertain and dynamic environment. The robotic system is supportedby a reasoning agent which makes the control action reactive and context-sensitive. The investigation is motivated by the future Human-Robot collaboration, therefore, it focuses on minimizing or avoiding collisions within the robot and the surroundings objects. The report describes the developed control architecture, which, in its modular and hierarchical structure, combines knowledge from different areas such as control theory, path and trajectory planning, computer vision, collision avoidance, and decision-making theory. The software is implemented in a ROS framework, in order to support a clear and modular design, suitable for future extensions and integration on different hardware components. The experiments are run on both real and simulated systems. The results show an autonomous robot capable of continuously adapting its movements despite the external agent interruptions, with a 99% success rate. We can conclude that an adaptive robotic system capable of performing constrained tasks and simultaneously reacting to external stimuli in an uncertain and dynamic environment is potentially obtainable.

AB - This paper presents a preliminary robotic solution for constrained teleoperation tasks in an uncertain and dynamic environment. The robotic system is supportedby a reasoning agent which makes the control action reactive and context-sensitive. The investigation is motivated by the future Human-Robot collaboration, therefore, it focuses on minimizing or avoiding collisions within the robot and the surroundings objects. The report describes the developed control architecture, which, in its modular and hierarchical structure, combines knowledge from different areas such as control theory, path and trajectory planning, computer vision, collision avoidance, and decision-making theory. The software is implemented in a ROS framework, in order to support a clear and modular design, suitable for future extensions and integration on different hardware components. The experiments are run on both real and simulated systems. The results show an autonomous robot capable of continuously adapting its movements despite the external agent interruptions, with a 99% success rate. We can conclude that an adaptive robotic system capable of performing constrained tasks and simultaneously reacting to external stimuli in an uncertain and dynamic environment is potentially obtainable.

KW - Rule-Based System

KW - Decision-Making

KW - Autonomous Robot

KW - Intelligent system

KW - Robot Control

KW - Constrained Motion Control

KW - ROS

U2 - 10.18178/ijmerr.8.3.393-400

DO - 10.18178/ijmerr.8.3.393-400

M3 - Journal article

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SP - 393

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JO - International Journal of Mechanical Engineering and Robotics Research

JF - International Journal of Mechanical Engineering and Robotics Research

SN - 2278-0149

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