Uatc, LLC

Uber Technologies, Inc.

Aurora Operations, Inc.

Utac, LLC

Joseph Lawrence Amato

Carlos Vallespi-Gonzalez

George Totolos, Jr

Hilton Keith Bristow

Nemanja Djuric

Shivam Gautam

Gregory P Meyer

Abhishek Mohta

Fang-Chieh Chou

Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.

Multiple stage image based object detection and recognition

Systems, methods, tangible non-transitory computer-readable media, and devices for operating an autonomous vehicle are provided. For example, the disclosed technology can include receiving sensor data and map data. The sensor data can include information associated with an environment detected by sensors of a vehicle. The map data can include information associated with traffic signals in the environment. Further, an input representation can be generated based on the sensor data and the map data. The input representation can include regions of interest associated with images of the traffic signals. States of the traffic signals in the environment can be determined, based on the input representation and a machine-learned model. Traffic signal state data that includes a determinative state of the traffic signals can be generated based on the states of the traffic signals.

Traffic signal state classification for autonomous vehicles

Object detection systems and methods can include identifying an object of interest within an image obtained from a camera, obtaining a first supplemental portion of data associated with the object of interest determining an estimated location of the object of interest within three-dimensional space based at least in part on the first supplemental portion of data and a known relative location of the camera, determining a portion of the LIDAR point data corresponding to the object of interest based at least in part on the estimated location of the object of interest within three-dimensional space, and providing one or more of at least a portion of the image corresponding to the object of interest and the portion of LIDAR point data corresponding to the object of interest as an output.

Image-based pedestrian detection

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Pittsburgh, PA, United States of America

Joseph Lawrence Amato