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Proceedings Paper

Machine perception and intelligent control architecture for multirobot coordination based on biological principles
Author(s): Stelios C.A. Thomopoulos; Grant Braught
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Paper Abstract

Intelligent control, inspired by biological and AI (artificial intelligence) principles, has increased the understanding of controlling complex processes without precise mathematical model of the controlled process. Through customized applications, intelligent control has demonstrated that it is a step in the right direction. However, intelligent control has yet to provide a complete solution to the problem of integrated manufacturing systems via intelligent reconfiguration of the robotics systems. The aim of this paper is to present an intelligent control architecture and design methodology based on biological principles that govern self-organization of autonomous agents. Two key structural elements of the proposed control architecture have been tested individually on key pilot applications and shown promising results. The proposed intelligent control design is inspired by observed individual and collective biological behavior in colonies of living organisms that are capable of self-organization into groups of specialized individuals capable of collectively achieving a set of prescribed or emerging objectives. The nervous and brain system in the proposed control architecture is based on reinforcement learning principles and conditioning and modeled using adaptive neurocontrollers. Mathematical control theory (e.g. optimal control, adaptive control, and neurocontrol) is used to coordinate the interactions of multiple robotics agents.

Paper Details

Date Published: 30 October 1996
PDF: 9 pages
Proc. SPIE 2905, Sensor Fusion and Distributed Robotic Agents, (30 October 1996); doi: 10.1117/12.256339
Show Author Affiliations
Stelios C.A. Thomopoulos, INTELNET Inc. (United States)
Grant Braught, INTELNET Inc. (United States)


Published in SPIE Proceedings Vol. 2905:
Sensor Fusion and Distributed Robotic Agents
Paul S. Schenker; Gerard T. McKee, Editor(s)

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