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Carnegie Mellon Robotics Institute

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Abstract

This paper describes an integrated MMW radar and vision sensor system for autonomous on-road navigation. The radar sensor has a range of approximately 200 metres and uses a linear array of receivers and wavefront reconstruction techniques to compute range and bearing of objects within the field of view. It is integrated with a vision based lane keeping system to accurately detect and classify obstacles with respect to the danger they pose to the vehicle and to execute required avoidance maneuvres.

Notes

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

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

Associated Project(s): Rapidly Adapting Lateral Position Handler

Text Reference

Dirk Langer and Todd Jochem, "Fusing Radar and Vision for Detecting, Classifying and Avoiding Roadway Obstacles," IEEE Symposium on Intelligent Vehicles, September, 1996.

BibTeX Reference

@inproceedings{Langer_1996_606,
   author = "Dirk Langer and Todd Jochem",
   title = "Fusing Radar and Vision for Detecting, Classifying and Avoiding Roadway Obstacles",
   booktitle = "IEEE Symposium on Intelligent Vehicles",
   month = "September",
   year = "1996",
}

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