Multi-Modal Interaction for Robotic Mules

Abstract

Today s soldier carries on average over 100lbs of gear, which takes its toll on the soldier and on the mission. To help mitigate this problem, the US Department of Defense is researching the use of robotic mules to move along with squads and help offload some of the excess weight carried by soldiers. The operator control units (OCUs) for these are typically portable computers with tele-operation or point-and-click interfaces. Instead, the DoD wants heads-up, hands-free methods of interaction that can fit seamlessly into the normal squad interaction patterns. This paper describes our research and prototyping in multi-modal interaction with robotic mules, focused on speech and gesture. We present an analysis of squad interactions to help determine the kind of technology useful for user input recognition. We describe an algorithm for gesture recognition using a 9-axis IMU, results of a formative evaluation, and a prototype multi-modal interface that can be used to command a robotic platform.

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Document Details

Document Type
Technical Report
Publication Date
Feb 26, 2014
Accession Number
ADA595822

Entities

People

  • Cory Dunham
  • Glenn Taylor
  • Matt Lanting
  • Mike Quist
  • Patrick Theisen
  • Paul Muench

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Computer Graphics
  • Computers
  • Department Of Defense
  • Human-Machine Interaction
  • Inertial Measurement Units
  • Language
  • Magnetic Fields
  • Measurement
  • Platforms
  • Prototypes
  • Recognition
  • Teleoperation
  • Test And Evaluation
  • Unmanned Vehicles
  • Wireless Communications

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Speech Processing/Speech Recognition.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy