Microsoft Technology Licensing, LLC

Ashley Nathan Feniello

Graham Arthur Wheeler

Danny B Lange

Nicolas Mai

Didier Coussemaeker

Adrien Felon

Joseph Futty

Sumit Gulwani

David Michael Callaghan

Russell Irvin Sanchez

Malek M Chalabi

Stan Birchfield

Hao Dang

Jean Sebastien Fouillade

Mark Scott Tonkelowitz

Charles F Olivier, Iii

Jordan Correa

Joe Futty

Robotic task program synthesis embodiments are presented that generally synthesize a robotic task program based on received examples of repositioning tasks. In one implementation, the exemplary repositioning tasks are human demonstrations of object manipulation in an actual or displayed robot workspace. A domain specific language (DSL) designed for object repositioning tasks is employed for the robotic control program. In general, candidate robotic task programs are generated from the example tasks. Each candidate program includes instructions for causing the robot to reposition objects, and represents a different permutation of instructions consistent with the received example tasks. The candidate programs are ranked, and whenever the top ranking program accomplishes the repositioning specified in each example task, it is designated as the synthesized robotic task program.

Program synthesis for robotic tasks

A robot is provided that includes a processor executing instructions that generate an image. The robot also includes a depth sensor that captures depth data about an environment of the robot. Additionally, the robot includes a software component executed by the processor configured to generate a depth map of the environment based on the depth data. The software component is also configured to generate the image based on the depth map and red-green-blue (RGB) data about the environment.

Computer vision system and method using a depth sensor

To accommodate different types and versions of execution environments on mobile devices, requests for applications from a programmable device, such as a smart phone or other mobile device include status data about the characteristics of the device. Information about the display, memory, storage, and/or script engine may be forwarded with a request. At a fulfillment server, the information is evaluated so that an appropriately versioned and configured application can be custom built, or selected from a pre-built inventory of applications. This allows a user to postpone an upgrade and still receive appropriate versions of executable, optimized to the particular mobile device.

Device dependent on-demand compiling and deployment of mobile applications

This disclosure describes data conversion and techniques for sending and receiving data at a mobile device. In one implementation, a proxy server may receive data from a mobile device. The proxy server may convert the data and send the converted data to a network service. In another implementation, a mobile device may convert data and send that data to a network service. The network service may generate data in response and send that data to the mobile device directly.

Efficient transform from XML to javascript objects

Selectively caching content related to routing data in a computing device. Prior to traversing a route, one or more access points to a network are identified. An expected level of access to a network (e.g., signal strength) along the route is determined. Portions of the route are selected based on the expected level of access. Content corresponding to at least one of the selected portions is received and stored for access during traversal of the route. For example, map images for areas expected to have poor network connectivity are cached prior to traversing the route to ensure that routing data is displayed to a user when in those areas. During transversal of the route, content is obtained and cached if a current level of access is less than a defined threshold.

Caching navigation content for intermittently connected devices

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Woodinville, WA, United States of America

Ashley Nathan Feniello