Waymo LLC

Google Inc.

Nuro Corp.

Electronic Arts Inc.

Russell Leigh Smith

Jiajun Zhu

Nathaniel Fairfield

Christopher Paul Urmson

Dirk Haehnel

Jamal Izadian

John Tisdale

Craig Lewin Robinson

Seth Michael LaForge

David Ian Ferguson

Peter Craig Lombrozo

Daniel Lynn Larner

Adam S Brown

Andrew Barton-Sweeney

Edward Daniel McCloskey

Carsten Jensen

Nick Vines

Daniel Ratner

Timothy Campbell

Hao Li

Tim Campbell

Peter Jon Kardassakis

Lacoursiere Claude

Jingqing Huang

Zachary Odenheimer

Jamal Isadian

Edward Daniel Mccloskey

A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

System and method for evaluating the perception system of an autonomous vehicle

A plurality of radar units is included in an overall radar module such that the plurality of radar units effectively cooperates to provide an approximately 360-degree field-of-view over a relatively long range. The overall radar module may include a ring-shaped printed circuit board, and a rim that includes multiple radar units positioned to substantially cover a 360-degree field-of-view. Radar units of the overall radar module may be grouped together such that two or more radar units may operate substantially synchronously, e.g., as a substantially single radar unit.

Methods and apparatus for providing a 360-degree field-of-view radar system

A method is provided that includes a vehicle receiving data from an external computing device indicative of at least one other vehicle in an environment of the vehicle. The vehicle may include a sensor configured to detect the environment of the vehicle. The at least one other vehicle may include at least one sensor. The method also includes determining a likelihood of interference between the at least one sensor of the at least one other vehicle the sensor of the vehicle. The method also includes initiating an adjustment of the sensor to reduce the likelihood of interference between the sensor of the vehicle and the at least one sensor of the at least one other vehicle responsive to the determination.

Methods and systems for vehicle radar coordination and interference reduction

According to one aspect, a relatively low-cost sensor for use on an autonomous vehicle is capable of detecting moving objects in a range or a zone that is between approximately 80 meters and approximately 300 meters away from the autonomous vehicle. A substantially single fan-shaped light beam is scanned for a full 360 degrees in azimuth. Using frequency-modulated-continuous-wave (FMCW) or phase coded modulation on the beam, with back end digital signal processing (DSP), moving objects may effectively be distinguished from a substantially stationary background.

Single beam digitally modulated lidar for autonomous vehicle distance sensing

Example systems and methods are disclosed for determining vehicle pose data for an autonomous vehicle. The vehicle computer system may receive pose data from multiple pose measurement systems of the autonomous vehicle. Each pose measurement system may include one or more corresponding sensors of the autonomous vehicle. The vehicle computer system may determine a pose data quality for the received pose data for each pose measurement system. The vehicle computer system may set the vehicle pose data to the pose data of the pose measurement system with the highest pose data quality. The vehicle computer system may control the autonomous vehicle based on the vehicle pose data.

System and method for determining pose data for a vehicle

An autonomous robotic vehicle includes a chassis, wheels movably mounted to the chassis by a suspension system, and a vehicle pose system. The vehicle pose system includes a ride height sensor system, a processor, and memory. The sensor system is configured to measure wheel displacement of the wheels relative to the chassis. The sensor system includes ride height sensors that determine wheel positions of the wheels with respect to the chassis as the vehicle travels along a surface. The memory has instructions stored thereon which, when executed by the processor cause the vehicle pose system to determine a plane of the surface corresponding to the wheel positions so that the pose system can determine a pose of the vehicle based on an angle of the surface with respect to the vehicle.

Determining vehicle pose using ride height sensors

An autonomous robot vehicle includes a front side and an energy absorbing system. The front side includes a front bumper and a front face including a frame defining a cavity. The energy absorbing system includes an energy absorbing member mounted in the cavity of the frame, and an inflatable airbag. The energy absorbing member is configured to reduce impact on an object struck by the autonomous robot vehicle. The inflatable airbag is mounted on the front side of the autonomous robot vehicle such that when the inflatable airbag is deployed, the inflatable airbag is external to the autonomous robot vehicle.

Hardware and software mechanisms on autonomous vehicle for pedestrian safety

Disclosed herein are systems for navigating an autonomous or semi-autonomous fleet comprising a plurality of autonomous or semi-autonomous vehicles within a plurality of navigable pathways within an unstructured open environment.

Fleet of autonomous vehicles with lane positioning and platooning behaviors

Integrated MIMO and SAR radar antenna

Growing community of inventors

Mountain View, CA, United States of America

Russell Leigh Smith