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Carnegie Mellon Robotics Institute

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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

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Field Robotics Center

Associated Lab(s) / Group(s): NavLab

Associated Project(s): Transit Bus Collision Warning Systems, Simultaneous Localization and Mapping with Detection, Tracking, and Classification of Moving Objects, Side Collision Warning System for Transit Buses, CTA Robotics

Number of pages: 13

Text Reference

Romuald Aufrere, Jay Gowdy, Christoph Mertz, Chuck Thorpe, Chieh-Chih Wang, and Teruko Yata, "Perception for collision avoidance and autonomous driving," Mechatronics, Vol. 13, No. 10, December, 2003, pp. 1149-1161.

BibTeX Reference

@article{Aufrere_2003_4507,
   author = "Romuald Aufrere and Jay Gowdy and Christoph Mertz and Chuck Thorpe and Chieh-Chih Wang and Teruko Yata",
   title = "Perception for collision avoidance and autonomous driving",
   journal = "Mechatronics",
   pages = "1149-1161",
   month = "December",
   year = "2003",
   volume = "13",
   number = "10",
}

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