wei-min Shen USC ISI paper Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms

weimin Shen's paper

Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms

Wei-Min Shen, Peter Will, Aram Galstyan, and Cheng-Ming Chuong. Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms. Autonomous Robots, 17(1):93–105, July 2004.

Download

Self-Organization through Digital Hormones

Wei-Min Shen. Self-Organization through Digital Hormones. IEEE Intelligent Systems, 18(4):81–83, 2003.

[933.5kB pdf]

Abstract

The control of robot swarming in a distributed manner is a difficult problem because global behaviors must emerge as a result of many local actions. This paper uses a bio-inspired control method called the Digital Hormone Model (DHM) to control the tasking and executing of robot swarms based on local communication, signal propagation, and stochastic reactions. The DHM model is probabilistic, dynamic, fault-tolerant, computationally efficient, and can be easily tasked to change global behavior. Different from most existing distributed control and learning mechanisms, DHM considers the topological structure of the organization, supports dynamic reconfiguration and self-organization, and requires no globally unique identifiers for individual robots. The paper describes the DHM and presents the experimental results on simulating biological observations in the forming of feathers, and simulating wireless communicated swarm behavior at a large scale for attacking target, forming sensor networks, self-repairing, and avoiding pitfalls in mission execution.

BibTeX Entry

@Article{   shen2004hormone-inspired-self-organization-and-distributed-control,
abstract = {The control of robot swarming in a distributed manner is a
   difficult problem because global behaviors must emerge as a
   result of many local actions. This paper uses a
   bio-inspired control method called the Digital Hormone
   Model (DHM) to control the tasking and executing of robot
   swarms based on local communication, signal propagation,
   and stochastic reactions. The DHM model is probabilistic,
   dynamic, fault-tolerant, computationally efficient, and can
   be easily tasked to change global behavior. Different from
   most existing distributed control and learning mechanisms,
   DHM considers the topological structure of the
   organization, supports dynamic reconfiguration and
   self-organization, and requires no globally unique
   identifiers for individual robots. The paper describes the
   DHM and presents the experimental results on simulating
   biological observations in the forming of feathers, and
   simulating wireless communicated swarm behavior at a large
   scale for attacking target, forming sensor networks,
   self-repairing, and avoiding pitfalls in mission execution.
   },
author = {Wei-Min Shen and Peter Will and Aram Galstyan and
   Cheng-Ming Chuong},
journal = {Autonomous Robots},
keywords = { self organization, self-reconfiguration, modular
   robots, distributed control, robot swarms, digital
   hormones},
month  = jul,
number = {1},
pages  = {93--105},
title  = {Hormone-Inspired Self-Organization and Distributed Control
   of Robotic Swarms},
volume = {17},
year  = {2004}
}