Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study

Carmelo Mineo, Quang-Cuong Pham, Jinchang Ren, Carmelo Mineo, Jaime Zabalza, Yijun Yan, Cuebong Wong, Tony Rodden, Zixiang Fei, Jorn Mehnen, Erfu Yang

Risultato della ricerca: Conference contribution

2 Citazioni (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 machine 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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pagine790-800
Numero di pagine11
Stato di pubblicazionePublished - 2018

Serie di pubblicazioni

NomeLECTURE NOTES IN ARTIFICIAL INTELLIGENCE

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
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