Home/Dependable Perception for Robots

Dependable Perception for Robots

Chuck Thorpe, Olivier Clatz, David Duggins, Jay Gowdy, Robert MacLachlan, James Ryan Miller, Christoph Mertz, Mel Siegel, Chieh-Chih Wang and Teruko Yata
Conference Paper, Carnegie Mellon University, Proceedings of International Advanced Robotics Programme IEEE, May, 2001

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

The weakest link in many mobile robots is perception. In order to build robots that are reliable and dependable and safe, we need to build robots that can see. Perception is becoming a solved problem for certain constrained environments. But for robots working outdoors, and at high speeds, and in close proximity to people, perception is still incomplete. Our robots need to see objects; to detect motion; and to detect which of those objects are people. In the current state of the art, this requires multiple sensors and multiple means of interpretation. This paper illustrates those principles in the context of the CMU Navlab Group’s work on vehicle safety for busses and passenger cars.

BibTeX Reference
@conference{Thorpe-2001-8214,
title = {Dependable Perception for Robots},
author = {Chuck Thorpe and Olivier Clatz and David Duggins and Jay Gowdy and Robert MacLachlan and James Ryan Miller and Christoph Mertz and Mel Siegel and Chieh-Chih Wang and Teruko Yata},
booktitle = {Proceedings of International Advanced Robotics Programme IEEE},
publisher = {Robotics and Automation Society},
school = {Robotics Institute , Carnegie Mellon University},
month = {May},
year = {2001},
address = {Pittsburgh, PA},
}
2017-09-13T10:45:46+00:00