Robust Behavior-Based Control for Distributed Multi-Robot Collection Tasks

Abstract

We demonstrate the effectiveness of behavior-based control in facilitating the development and evaluation of multi-robot controllers that are: (1) robust to robot failures, and(2) easily modified to facilitate development of the controller variation that sufficiently satisfies the design requirements for the task. Our experimental focus here is distributed multi-robot collection, a class of tasks that includes de-mining and toxic waste clean-up. We demonstrate a basic multi-robot controller for the collection task, then show how to easily derive two spatio-temporal variations with markedly different performance properties. We evaluate the desirability of these controllers with respect to design requirements involving inter-robot interference, time-to-completion, and energy expenditure. The data for evaluation come from experiments using four physical mobile robots performing the three variations of the collection task.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
AD1020823

Entities

People

  • Dani Goldberg
  • Maja Matarić

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Actuators
  • Boundaries
  • Collisions
  • Complex Systems
  • Computational Science
  • Computer Science
  • Computers
  • Damage Detection
  • Detection
  • Detectors
  • Hierarchies
  • Infrared Detectors
  • Radio Equipment
  • Robotic Swarms
  • Robotics
  • Robots
  • Simulations

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy
  • Autonomy - Autonomous System Control