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    Self-Driving Cars That Recognize Free Space Can Better Detect Objects

    Article obtained from Photonics RSS Feed.

    Researchers at Carnegie Mellon University (CMU) have demonstrated that they can significantly improve detection accuracy in self-driving cars by helping the vehicle recognize what it does not see.

    Self-driving vehicles use 3D data from lidar to represent objects as a point cloud and then try to match those point clouds to a library of 3D representations of objects. The problem with that, according to Peiyn Hu, a Ph.D. student in CMU’s Robotics Institute, is that the 3D data from the vehicle’s lidar isn’t exactly 3D — the sensor can’t see the occluded parts of an object, and current algorithms don’t reason about such occlusions.
    New CMU research shows that what a self-driving car doesn’t…

    Jun, 16 2020 |

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