Waymo LLC

Digital Dream Labs, LLC

Kevin Yoon

Hanns W Tappeiner

Lee Crippen

Daniel Thomas Casner

David W Smith

David Smith

Vadim Butakov

Anthony Armenta

A method includes identifying map data comprising driving constraint data for a route of an autonomous vehicle (AV), the map data being of a road network associated with the route of the AV, the driving constraint data being based on physical vehicle data. The method further includes, while the AV is travelling the route, identifying current environmental sensing data for a portion of the route. The method further includes causing, based on the map data comprising the driving constraint data for the route and the current environmental sensing data associated with the portion of the route, the AV to travel the portion of the route.

Physics-informed optimization for autonomous driving systems

An autonomous vehicle is provided that includes one or more sensors coupled to the autonomous vehicle, and a computing device configured to: (i) receive, from the one or more sensors, operational data related to an operation of the autonomous vehicle, (ii) receive geographical data related to an anticipated route of the autonomous vehicle, (iii) generate, for the anticipated route and based on the operational data and the geographical data, an operational response model representing respective operational constraints for one or more operational parameters of the autonomous vehicle, wherein values for the one or more operational parameters are represented along coordinate axes of a geometrical shape, and wherein the one or more operational parameters are mutually coupled to each other, and (iv) responsively execute, based on the operational response model, an autonomous control strategy comprising one or more adjustments to the operation of the vehicle within the respective operational constraints.

Operational response model based on operational parameters

A method includes identifying, based on grade data of a route of an autonomous vehicle (AV), a segment of the route that has a grade value that meets a threshold grade value. Responsive to identifying the segment, the method further includes generating, based on the grade data and physical vehicle data of the AV, driving constraint data for the segment of the route. The method further includes causing a routing module of the AV to generate, based on the driving constraint data for the segment of the route, short time horizon routing data corresponding to a portion of the segment. The AV is to travel the portion of the segment of the route based on the short time horizon routing data.

This specification relates to robots and audio processing in robots. In general, one innovative aspect of the subject matter described in this specification can be embodied in a robot that includes: a body and one or more physically moveable components; a plurality of accessory input subsystems and one or more other sensor subsystems; one or more processors; and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the robot to perform operations. The operations can include: receiving one or more sensor inputs from the one or more other sensor subsystems; determining a predicted direction of a detected sound emitter based on the one or more sensor inputs of the one or more other sensor subsystems; calculating a spatial filter based on the predicted direction; obtaining, by the plurality of accessory input subsystems, respective audio inputs; and processing the respective audio inputs according to the calculated spatial filter.

Spatial acoustic filtering by a mobile robot

This specification relates to robots and audio processing in robots. One aspect of the subject matter includes: a body and one or more physically moveable components; a plurality of microphones; one or more processors; and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the robot to perform operations. The operations can include: obtaining map data of an environment of the robot; selecting a test location from the map data; navigating to the selected test location; receiving a sound wave propagating through the environment of the robot; computing one or more acoustic transfer functions for the test signal, wherein each acoustic transfer function represents how the test signal was transformed by the environment of the robot during its propogation through the environment of the robot; and storing each of the transfer functions in association with the test location.

Map related acoustic filtering by a mobile robot

This specification relates to robots and audio processing in robots. In general, one innovative aspect of the subject matter described in this specification can be embodied in a robot that includes: a body and one or more physically moveable components; a plurality of microphones and one or more other sensor subsystems; one or more processors; and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the robot to perform operations. The operations can include: receiving one or more sensor inputs from the one or more other sensor subsystems; determining a predicted direction of a detected sound emitter based on the one or more sensor inputs of the one or more other sensor subsystems; calculating a spatial filter based on the predicted direction; obtaining, by the plurality of microphones, respective audio inputs; and processing the respective audio inputs according to the calculated spatial filter.

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Oakland, CA, United States of America

Kevin Yoon