Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.

Conference

ConferenceThe 9th International Conference on Brain-Inspired Cognitive System​
Abbreviated titleBICS2018
CountryChina
CityXi'an
Period7/07/188/07/18
Internet address

Fingerprint

Industrial robots
Robots
Cameras
Degrees of freedom (mechanics)
Real time systems
Motion planning
Computer vision
Industrial applications
Manipulators
Robotics
Lighting
Color
Sensors
Costs

Keywords

  • machine vision
  • path planning
  • robot control
  • adaptive reasoning
  • dynamic environment
  • autonomous systems
  • robotics

Cite this

@conference{181cf5a0edc04a5fb1f7193fb75456e6,
title = "Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study",
abstract = "In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.",
keywords = "machine vision, path planning, robot control, adaptive reasoning, dynamic environment, autonomous systems, robotics",
author = "Jaime Zabalza and Zixiang Fei and Cuebong Wong and Yijun Yan and Carmelo Mineo and Erfu Yang and Tony Rodden and Jorn Mehnen and Quang-Cuong Pham and Jinchang Ren",
year = "2018",
month = "7",
day = "7",
language = "English",
pages = "1--10",
note = "The 9th International Conference on Brain-Inspired Cognitive System​, BICS2018 ; Conference date: 07-07-2018 Through 08-07-2018",
url = "http://bics2018.org/",

}

Zabalza, J, Fei, Z, Wong, C, Yan, Y, Mineo, C, Yang, E, Rodden, T, Mehnen, J, Pham, Q-C & Ren, J 2018, 'Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study' Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China, 7/07/18 - 8/07/18, pp. 1-10.

Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments : a case study. / Zabalza, Jaime; Fei, Zixiang; Wong, Cuebong; Yan, Yijun; Mineo, Carmelo; Yang, Erfu; Rodden, Tony; Mehnen, Jorn; Pham, Quang-Cuong ; Ren, Jinchang.

2018. 1-10 Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments

T2 - a case study

AU - Zabalza, Jaime

AU - Fei, Zixiang

AU - Wong, Cuebong

AU - Yan, Yijun

AU - Mineo, Carmelo

AU - Yang, Erfu

AU - Rodden, Tony

AU - Mehnen, Jorn

AU - Pham, Quang-Cuong

AU - Ren, Jinchang

PY - 2018/7/7

Y1 - 2018/7/7

N2 - In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.

AB - In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.

KW - machine vision

KW - path planning

KW - robot control

KW - adaptive reasoning

KW - dynamic environment

KW - autonomous systems

KW - robotics

M3 - Paper

SP - 1

EP - 10

ER -