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Perception for collision avoidance and autonomous driving
Authors:Romuald Aufr  re, Jay Gowdy, Christoph Mertz, Chuck Thorpe, Chieh-Chih Wang,Teruko Yata
Affiliation:

The Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA

Abstract:The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, a map-based fusion system, and a probability based predictive model. The complete system has been demonstrated on the Navlab 11 vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, detecting and tracking fixed objects, moving objects, pedestrians, curbs, and roads.
Keywords:Collision avoidance   Autonomous driving   Short-range surround sensing   Optical flow   Triangulation laser sensor   Curb detection   LIDAR object detection   Sensor fusion   Collision prediction
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