Zoox, Inc.

Stanley L Volta

Allan Zelener

Francesco Papi

Qian Song

Techniques for segmenting sensor data are discussed herein. Data can be represented in individual levels in a multi-resolution voxel space. A first level can correspond to a first region of an environment and a second level can correspond to a second region of an environment that is a subset of the first region. In some examples, the levels can comprise a same number of voxels, such that the first level covers a large, low-resolution region, while the second level covers a smaller, higher-resolution region, though more levels are contemplated. Operations may include analyzing sensor data represented in the voxel space from a perspective, such as a top-down perspective. From this perspective, techniques may generate masks that represent objects in the voxel space. Additionally, techniques may generate segmentation data to verify and/or generate the masks, or otherwise cluster the sensor data.

Multi-resolution top-down segmentation

Techniques for determining detection boxes representing objects in an environment using pixel clustering are disclosed herein. Autonomous vehicle sensors can capture data in an environment that may include separate objects, such as large and/or articulated vehicles. In an example, the data can include a plurality of pixels that are associated with a large object. A vehicle computing system can generate a detection box for each pixel of the plurality of pixels and can determine at least one averaged detection box representing the large object. In an example, the vehicle computing system can control the vehicle based in part on the at least one averaged detection boxes.

Detection clustering

A computer implemented method. Includes: obtaining, from a sensor system onboard a vehicle, a plurality of hypotheses for an orientation of an object in a vicinity of the vehicle, relative to a coordinate system of the vehicle; estimating, based on the plurality of hypotheses, values of a probability distribution for the orientation of the object at a plurality of candidate orientations; and estimating, based at least in part on the estimated values of the probability distribution at the plurality of candidate orientations, the orientation of the object relative to the coordinate system.

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Foster, CA, United States of America

Stanley L Volta