Home /Research /Dependable Perception for Robots
PERCEPTION

Dependable Perception for Robots

Chuck Thorpe, Olivier Clatz, David Duggins, Jay Gowdy, Robert A. MacLachlan, John Miller, Christoph Mertz, Mel Siegel, Chieh‐Chih Wang, Teruko Yata

Year
2018
Citations
14

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.

Keywords

RobotPerceptionMobile robotComputer scienceHuman–computer interactionContext (archaeology)Artificial intelligenceComputer visionPsychologyGeography

Related papers

Browse all PERCEPTION papers