Mixed-Initiative Control of Autonomous Unmanned Units Under Uncertainty

Abstract

The MICA program focused on changing the control and coordination of unmanned aerial vehicles from a need for two to four persons per vehicle to one person controlling five or more vehicles. This program developed techniques for hierarchical control using mixed-initiative planning guidance and control taking a number of kinds of uncertainty into account at a fundamental level. These techniques focused on reasoning about uncertainty, including planning, belief tracking and communications with both human and automation. We developed this control model using Partially Observable Markov Decision Processes. The mixed-initiative interactions enabled users to describe constraints at multiple levels of the planning hierarchy. Techniques include visualization of the environment and optional speech input. The capabilities were demonstrated in a laboratory environment and on the program's Open Experimental Platform.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2006
Accession Number
ADA446039

Entities

People

  • David Diller
  • Dieter Fox
  • Geoffrey Gordon
  • Mark Burstein
  • Sebvastian Thrun

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Biomedical
  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Aircrafts
  • Artificial Intelligence
  • Computational Science
  • Control Systems
  • Game Theory
  • Guidance
  • Hierarchies
  • Information Processing
  • Information Systems
  • Multiagent Systems
  • Sequential Monte Carlo Methods
  • Simultaneous Localization And Mapping
  • Situational Awareness
  • Unmanned Aerial Vehicles
  • Unmanned Vehicles
  • Visualizations

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Artificial Intelligence

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - Human-Robot Interaction