|LIDAR and Vision Sensor Fusion for Autonomous Vehicle Navigation
The goal of this project is to investigate methods for combining laser range sensors (i.e., LIDARs) with visual sensors (i.e., video cameras) to improve the capabilities of autonomous vehicles.
|Real-time Lane Tracking in Urban Environments
The purpose of this project is to develop methods for the real-time detection and tracking of lanes and intersections in urban scenarios in order to support road following by an autonomous vehicle in GPS-denied situations.
|Tightly Integrated Stereo and LIDAR
The goal of this project is to use sparse, but accurate 3D data from LIDAR to improve the estimation of dense stereo algorithms in terms of accuracy and speed.
|Vehicle Localization in Naturally Varying Environments
The purpose of this project is to develop methods for place matching that are invariant to short- and long-term environmental variations in support of autonomous vehicle localization in GPS-denied situations.
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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