Intelligent systems for industrial robotics: Application in logistic field

  • Wang T
  • Ramik D
  • Sabourin C
 et al. 
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Purpose - Different machines are already present in the human environment, easing human beings' daily life. In the future, this tendency will be accentuated by integration of numerous robots (e.g. wheeled robots, legged robots, humanoid robots, network sensors, etc.) in the human environment. A wide range of applications, such as those dealing with warehouse management, industrial assembling, military applications, daily-life tasks, can benefit from multi-robot systems. The purpose of this paper is to propose an intelligent system for industrial robotics in the logistic field, based on collaboration between heterogeneous robots. Design/methodology/approach - The proposed infrastructure for this multi-robot system is composed of a robots' network including one humanoid robot, wheeled robots, cameras, and remote computer. All devices can communicate between them by using wireless network. The goal of the humanoid robot is to lead the wheeled robots according to the environment and wheeled robots are used to carry a load. The camera allows providing complementary information about the environment; and thanks to machine learning, this control strategy allows complex tasks to be perormed for these logistic applications. Findings - This concept is implemented on real robots within the frame of a demonstrator including the above-mentioned kind of robots. The preliminary results, obtained during experimentations, prove the feasibility of the presented strategy for real applications. Originality/value - The main originalities of this work are, on the one hand, the use of an heterogeneous multi-robots system for logistic tasks, and on the other hand, the proposed machine learning allows a collaboration task between heterogeneous robots in an autonomous manner. Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.

Author-supplied keywords

  • Artificial intelligence
  • Autonomous
  • Co-operating
  • Control
  • Industrial robotics
  • Intelligent systems
  • Logistic application
  • Machine learning
  • Multi-robot systems
  • Robot formation
  • Systems and control theory
  • Vision

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  • Ting Wang

  • Dominik M. Ramik

  • Christophe Sabourin

  • Kurosh Madani

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