STRIPE: Remote Driving Using Limited Image Data.

Abstract

Driving a vehicle, either directly or remotely, is an inherently visual task. When heavy fog limits visibility, we reduce our car's speed to a slow crawl, even along very familiar roads. In teleoperation systems, an operator's view is limited to images provided by one or more cameras mounted on the remote vehicle. Traditional methods of vehicle teleoperation require that a real time stream of images is transmitted from the vehicle camera to the operator control station, and the operator steers the vehicle accordingly. For this type of teleoperation, the transmission link between the vehicle and operator workstation must be very high bandwidth (because of the high volume of images required) and very low latency (because delayed images can cause operators to steer incorrectly). In many situations, such a high-bandwidth, low-latency communication link is unavailable or even technically impossible to provide. Supervised TeleRobotics using Incremental Polyhedral Earth geometry, or STRIPE, is a teleoperation system for a robot vehicle that allows a human operator to accurately control the remote vehicle across very low bandwidth communication links, and communication links with large delays. In STRIPE, a single image from a camera mounted on the vehicle is transmitted to the operator workstation. The operator uses a mouse to pick a series of "waypoints" in the image that define a path that the vehicle should follow. These 2D waypoints are then transmitted back to the vehicle, where they are used to compute the appropriate steering commands while the next image is being transmitted. STRIPE requires no advance knowledge of the terrain to be traversed, and can be used by novice operators with only minimal training. STRIPE is a unique combination of computer and human control. The computer must determine the 3D world path designated by the 2D waypoints and then accurately

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA327036

Entities

People

  • Jennifer E. Kay

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Autonomous Systems
  • Cameras
  • Cognitive Systems Engineering
  • Collision Avoidance
  • Computer Science
  • Computers
  • Control Systems
  • Coordinate Systems
  • Dead Reckoning
  • Graphical User Interface
  • Human-Computer Interaction
  • Jet Propulsion
  • Psychology
  • Teleoperation
  • Three Dimensional
  • Two Dimensional
  • User Interface

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Computer Vision.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Human-Robot Interaction