Built Robotics Inc.

Google Inc.

Linus Page Chou

Noah Austen Ready-Campbell

Andrew Xiao Liang

Christian John Wawrzonek

Cyrus McMann Ready-Campbell

Edward Stephen Walker, Jr

Jacob Burton Matthews

James Lee Wogulis

Kasem Marifet

Mayur Venktesh Deshpande

James Hyunsoo Koh

Paul J Baker

Maciej Babinski

Jige Yu

Jonathan Klem

James Edward Stewart

Eric W Ewald

Amit Khanna

Andrey Petrov

Carolyn R Marshall

Paul Sliwowski

Edward Walker

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collects any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

Checking volume in an excavation tool

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

Excavating earth from a dig site using an excavation vehicle

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

Mapping a dig site diagram

Machine-implemented methods for validating a web site analytics configuration are provided. In one aspect, a method includes receiving, with a low latency web site traffic analytics and monitoring service, a registration for a web site, and sending an initial transmission to the registered web site, the transmission configured to generate a response transmission of web site traffic data to the analytics service. The method also includes outputting a notification indicating that the web site has been successfully registered with the analytics service when the traffic data is received by the analytics service, and outputting a notification indicating that the web site has not been successfully registered with the analytics service when the traffic data is not received by the analytics service. Systems, graphical user interfaces, and machine-readable media are also provided.

System for validating site configuration based on real-time analytics data

A system for user association attribution may include one or more processors and memory. The one or more processors may receive information pertaining to relationship events that each correspond to a participant and one of several entities in a social network, allocate, for each relationship event, attribution values to touchpoints accessed by the corresponding entity prior to the relationship event. The processors may further determine a weight for each of the attribution values allocated to each of the touchpoints, where the weight for each of the attribution values is based at least in part on each of the relationship events for which each of the attribution values was allocated, generate an aggregate attribution value for each of the touchpoints based at least in part on the weighted attribution values allocated to each of the touchpoints, and provide, to the participant, each aggregate attribution value generated for each of the touchpoints.

User association attribution system

Growing community of inventors

San Francisco, CA, United States of America

Linus Page Chou