Gm Cruise Holdings LLC

Glenn D Sweeney

Zhanping Xu

Robert Vets

Kartheek Chandu

Kaitlyn Williams

Justin DeCell

Philip David Aufdencamp

Aspects of the subject technology relate to systems, methods, and computer-readable media for identifying roll, pitch, and azimuth angles for an object based on surface normal vectors. Image data tracking a surface as an object moves relative to the surface can be accessed. A reference normal vector of the surface can be identified. A dynamic normal vector of the surface associated with the object moving over the surface can be identified from the image data. One or a combination of roll, pitch, and azimuth of the object with respect to the surface can be determined based on the reference normal vector and the dynamic normal vector.

Identifying stability of an object based on surface normal vectors

A sensor calibration evaluation system evaluates the quality of control point detection by translating a control object within a scene by a measured amount to generate a sequence of sensor views of the scene as the control object is translated by a known (measured) amount. The control points within each of the sequence of sensor views are detected with a control point detection algorithm. By detecting the control points and determining the detected movement of the control points, a correlation between the measured movement and detected movement can be determined and represent the quality of the control point detection given the set of detection conditions.

Linear movement for control point detection verification

Aspects of the subject technology relate to systems, methods, and computer-readable media for performing ground segmentation through formation of a single super voxel. Image data tracking a surface as an object moves relative to the surface is accessed. Samples of the image data is grouped into different subsets to form a plurality of subsets of the image data. A normal vector to a corresponding plane defined by each subset of the plurality of subsets of the image data are identified. The samples of the image data are re-grouped into a single subset of the image data based on the corresponding normal vector for each subset of the plurality of subsets of the image data. A surface plane representation of the surface is identified based on the single subset of the image data.

Ground segmentation through super voxel

The present technology pertains to validating a virtual camera in a simulation environment by utilizing an improved camera model to provide quantitative measurements of the model's performance. A method of validating a virtual camera in a simulation environment comprises presenting at least one reference chart in the simulated environment and capturing images of the reference chart in the simulated environment using a virtual camera. The method further includes interrupting an image pipeline of the virtual camera after at least one simulated process in the image pipeline to extract a RAW image. The method analyzes the RAW image to derive measurements of metrics to characterize the virtual camera. The measured metrics are compared to metrics of a calibrated real-world camera to verify that the metrics are within a threshold delta that is indicative that the virtual camera sufficiently approximates the real-world camera.

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Sebastopol, CA, United States of America

Glenn D Sweeney