Motion Coordination and Adaptation Using Deception and Human Interactions

Abstract

This project developed fundamental, new tools and techniques for how tostructure the coordination and control strategies in teams of mobile robots. In particular, two general thrust areas were pursued, focusing on human-swarm interactions and pursuit-evasion-based motion control strategies. Although interesting in their own rights, the unifying theme behind these two different thrusts is the notion of intent, where the first thrust, which can be thought of as evolving at a higher level of abstraction, focused on how user intent can be injected into a network of mobile agents in a fundamentally sound manner. The second thrust, in turn, focused on how the intent can be hidden in order to produce effective, deception-based coordination and pursuit strategies.

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Document Details

Document Type
Technical Report
Publication Date
Nov 18, 2016
Accession Number
AD1022814

Entities

People

  • Magnus Egerstedt
  • Panagiotis Tsiotras

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Autonomous Systems
  • Autonomous Underwater Vehicles
  • Computational Science
  • Differential Equations
  • Energy Consumption
  • Equations Of Motion
  • Guidance
  • Human Systems Integration
  • Human-Robot Interaction
  • Human-Swarm Interaction
  • Motion Planning
  • Partial Differential Equations
  • Robotic Swarms
  • Robots
  • Unmanned Aerial Vehicles
  • Unmanned Vehicles

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Sensor Fusion and Tracking Systems.

Technology Areas

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