Intrinsic Innovation LLC

X Development LLC

Gregory Prisament

Michael Beardsworth

Alan S Thompson

Yuchen Wu

Laura Stoia

Sean Alexander Cassero

Andre Gaschler

Nicholas Julian Cox

Nils Berg

Benjamin Bremer

Marcin Krzysztof Szczodrak

Dmytro Hrybenko

Abhishek Shailesh Shah

Asa Kaplan

Karsten Knese

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a real-time robotics control framework that implements a real-time clock with transferable ownership. One of the systems being configured to operate a real-time control loop for a robot in multiple modes include a base mode and an augmented mode, wherein when operating the robot in the base mode, the system is configured to operate a base real-time control loop in which a start of each tick of the base real-time control loop is initiated by a real-time software control module, and wherein when operating the robot in the augmented mode, the system is configured to operate multiple real-time control loops comprising the base real-time control loop and a robot real-time control loop in which a start of each tick of the real-time control loop is initiated by the real-time software drive module.

Transferable real-time clock for robotics control

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling a robot to perform a custom real-time action that uses a callback function. One of the methods comprises receiving a definition of a custom real-time control function that specifies a custom callback function, an action, and a custom reaction that references the custom callback function; providing a command to initiate the action; repeatedly executing, by the control layer of the real-time robotics control framework, the custom real-time control function at each tick of a real-time robotics system driving one or more physical robots, including: obtaining current values of one or more state variables, evaluating the custom reaction specified by the custom real-time control function according to the current values of the one or more state variables, and whenever the one or more conditions of the custom reaction are satisfied, invoking the custom callback function.

Real-time robotics control framework

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling a robot to perform a custom real-time action that uses streaming inputs. One of the methods comprises receiving a definition of a custom real-time streaming control function that defines a custom streaming action, wherein the custom streaming action specifies a goal state for a robot in an operating environment; providing a command to initiate the custom streaming action; and repeatedly providing updated goal states for the custom streaming action, wherein the control layer of the framework is configured to execute the custom streaming action including driving the robot toward a most recent goal state at each tick of a real-time robotics control cycle.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing real-time code analysis. One of the methods includes receiving a request to perform real-time code analysis on source code, wherein the request identifies one or more target source code elements. A plurality of real-time annotation values occurring in the source code for the target source code elements are identified. A call graph is generated for the one or more target source code elements. The call graph is traversed to identify one or more real-time violations, wherein each real-time violation is an instance in the source code that violates one or more real-time safe criteria. An output is provided that identifies one or more of the real-time violations occurring in the source code.

Analysis of real-time software

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for logging real-time data of a robot control system. One of the systems comprises a real-time robotic control system comprising one or more computers, programmed to perform operations comprising i) software module loops and ii) real-time data logging, wherein each software module loop comprises a plurality of software modules executed repeatedly in a predetermined sequence, each software module executes within a predetermined time window, and the real-time data logging comprises copying segments of real-time data used by a particular software module to a buffer accessible by a non-real-time downstream system, wherein each segment of real-time data is copied at a respective predetermined time relative to execution of the software modules in the software module loop; and the non-real-time downstream system comprising one or more computers, the non-real-time downstream system programmed to perform operations that consume the real-time messages.

Data logger for a real-time robotic control system

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a composability framework that supports the coordination of the low-level actions of multiple subsystems. One of the methods comprises receiving a multi-device application definition for a real-time robotic control system configured to perform operations comprising controlling a robotic execution environment having multiple robotic components, wherein the application definition comprises: one or more custom high-level software modules for each robotic component of the multiple robotic components; respective module interface definitions for each of the custom high-level software modules, wherein a module interface definition of a custom high-level software module specifies one or more asynchronous or real-time communication channels; and respective device interface definitions for each of the multiple robotic components; and processing the application definition to generate output programs to be executed respectively by the multiple robotic components.

Composability framework for robotic control system

Methods, apparatus, systems, and computer-readable media are provided for optimizing robot-implemented tasks based at least in part on historical task and location correlated duration data collected from one or more robots. Historical task and location correlated duration data may, in some implementations, include durations of different tasks performed in different locations by one or more robots in one or more particular environments, and knowledge of such durations may be used to optimize tasks performed by the same or different robots in the future.

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East Palo Alto, CA, United States of America

Gregory Prisament