HORMCOMM: Hormone-Inspired Cooperative Communication

Abstract

The control and communication of massive robot swarms in a distributed manner is a difficult problem because global behaviors must be emerged as a collection of many local actions. This project uses a biologically inspired control method called Digital Hormone Model (DHM) to control the communication, tasking, and execution of massive robot swarms based on local communication, signal propagation, and stochastic reactions. This model is probabilistic, dynamic, fault-tolerant, efficient in computation, and can be easily tasked to deal with topology changes in the communication network and modify the global behaviors. Different from most existing distributed control and learning mechanisms, the DHM considers the topological structure of the organization, and supports dynamic re-configuration and self-organization. In the last year, we have formalized the concept of DHM and conducted experiments of simulating swarm behaviors in large scale for target attacking, network formation, self-repair, and avoid pitfalls in mission execution.

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Document Details

Document Type
Technical Report
Publication Date
Dec 14, 2003
Accession Number
ADA422130

Entities

People

  • Wei-min Shen

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Animals
  • Autonomous Systems
  • Cells
  • Communication Networks
  • Computer Programs
  • Control Systems
  • Materials Science
  • Mobile Phones
  • Networks
  • Robotic Swarms
  • Robotics
  • Self Organizing Systems
  • Sensor Networks
  • Systems Biology
  • Task Forces
  • Wireless Communications
  • Wireless Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control