Zoox, Inc.

Zipline International Inc.

Jeremy Schwartz

Keenan A Wyrobek

Prateek Chandresh Shah

Andrew Chambers

Ryan Oksenhorn

Marin Kobilarov

Joseph Funke

Mark Jonathon McClelland

David Evan Zlotnik

Kazuhide Okamoto

Rick Zhang

Jacob Patrick Thalman

Olivier Toupet

Sriram Narayanan

Jack Riley

Liam Gallagher

Vincent Andreas Laurense

Wentao Zhong

Systems and techniques for determining a sideslip vector for a vehicle that may have a direction that is different from that of a heading vector for the vehicle. The sideslip vector in a current vehicle state and sideslip vectors in predicted vehicles states may be used to determine paths for a vehicle through an environment and trajectories for controlling the vehicle through the environment. The sideslip vector may be based on a vehicle position that is the center point of the wheelbase of the vehicle and may include lateral velocity, facilitating the control of four-wheel steered vehicle while maintaining the ability to control two-wheel steered vehicles.

Determining vehicle position using sideslip vector

Tracking perception and/or planning component decisions may comprise generating a data structure in association with an output determined by a component. This data structure, along with one or more data structures generated in association with other outputs generated by the same or different components of the vehicle, may be used to determine a trace that identifies component(s) that determined outputs that affected a particular component's generation of an output. This trace and/or factors identified by the data structure may be used to detect a problem with a component; identify a component or output therefrom that may be causing an error; determine a portion of a component that has been activated and a frequency associated therewith; and/or visualize operation of the vehicle associated with activation of particular components, among additional or alternate uses discussed herein.

Vehicle operation and/or simulation decision registry

Techniques for aggregating costs associated with one or more heat maps to control a vehicle in an environment are discussed herein. A vehicle computing device can implement a model to determine heat maps and respective cost information for different features of the environment based on sensor data. The vehicle computing device can output a planned trajectory for the vehicle based on combining the heat maps. The techniques can also include determining a rationalization or root cause detailing reasons why the planned trajectory was determined.

Optimization based planning system

An unmanned aircraft system includes an aircraft control system that enables the safe operation of multiple unmanned aerial vehicles in the same airspace, through the use of a decentralized air traffic management system. The decentralized air traffic management system is robust against loss of communication between the unmanned aerial vehicle and does not require a centralized ground control system to coordinate the vehicles.

Decentralized air traffic management system for unmanned aerial vehicles

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Redwood City, CA, United States of America

Jeremy Schwartz