Uber Technologies, Inc.

Aurora Operations, Inc.

Gm Global Technolgoy Operations, Inc.

Carnegie Mellon University

Karthik Lakshmanan

Ethan Eade

Brian C Becker

J Andrew Bagnell

Daniel Munoz

Samuel Sean

Jake Charland

Luona Yang

Arunprasad Venkatraman

Ragunathan Rajkumar

Paolo Giusto

Yuchen Xie

A method may include obtaining lidar data comprising a plurality of lidar returns from an environment of an autonomous vehicle. The lidar data may be processed with a machine learning model to generate, for the plurality of lidar returns, a plurality of first outputs that each identify a respective lidar return as belonging to an object or non-object and a plurality of second outputs that identify lidar returns belonging to objects as harmful or non-harmful to the autonomous vehicle. A subset of the lidar returns identified as belonging to objects that (i) do not correspond to any of a plurality of pre-classified objects and (ii) were identified as harmful to the autonomous vehicle may be determined. The autonomous vehicle may be controlled based at least in part on the subset of lidar returns.

System and method for generating information on remainder of measurement using sensor data

A method may include obtaining sensor data that include a plurality of sensor returns from an environment of an autonomous vehicle. A first set of features may be extracted from the sensor data. The first set of features may be processed with a machine learning model to generate, for at least a subset of the plurality of sensor returns, a first output that classifies a respective sensor return as corresponding to an object or non-object and a second output that indicates a property of the object. The sensor returns classified as corresponding to objects may be compared to a plurality of pre-classified objects to generate one or more generic object classifications. The autonomous vehicle may be controlled based at least in part on the one or more generic object classifications.

The present disclosure provides systems and methods for tracking vehicles or other objects that are perceived by an autonomous vehicle. A vehicle filter can employ a motion model that models the location of the tracked vehicle using a vehicle bounding shape and an observation model that generates an observation bounding shape from sensor observations. A dominant vertex or side from each respective bounding shape can be identified and used to update or otherwise correct one or more predicted shape locations associated with the vehicle bounding shape based on a shape location associated with the observation bounding shape.

Systems and methods to track vehicles proximate perceived by an autonomous vehicle

Managing task execution in a multi-core processor may be achieved by employing a spinlock and a multi-processor priority ceiling protocol. The spinlock may be employed to effect a dynamically enforceable mutual exclusion constraint. The multi-processor priority ceiling protocol may be employed to effect the dynamically enforceable mutual exclusion constraint to synchronize a plurality of tasks executing in the first and second processing cores of the multi-core processor.

Method and apparatus for improving processing performance of a multi-core processor

Growing community of inventors

Pittsburgh, PA, United States of America

Karthik Lakshmanan