Xerox Corporation

Palo Alto Research Center Inc.

Shiwali Mohan

Matthew Klenk

Kent J Evans

Matthew Adam Shreve

John Turner Maxwell, Iii

Aaron Ang

Victoria M Bellotti

Robert Roy Price

Filip Dvorak

One embodiment can provide a system for augmenting perceptions of a machine sensing system. During operation, one or more sensors of the system can obtain sensory information associated with a physical system. The system can determine a state of a first component of the physical system based on the obtained sensory information; select, from a rule database, one or more logical rules associated with at least the first component; and augment a perception of the machine sensing system toward the physical system based on both the determined state of the first component and the selected one or more logical rules, thereby facilitating the machine sensing system to make a decision associated with the physical system.

Method and system for rule-based augmentation of perceptions

A method is provided. The method includes obtaining a state graph that represents a set of objects within an environment and a set of positions of the set of objects within the environment. The state graph includes a set of object nodes and a set of property nodes. The method also includes obtaining user input data. The user input data is generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes providing the enhanced state graph to a planning module. The planning modules generates instructions for operating a mechanical system based on the enhanced state graph.

Interacting with machines using natural language input and an enhanced state graph

In one embodiment, a method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes determining a set of positions of the set of objects and a set of properties of the set of objects based on the sensor data. The method further includes generating a state graph based on the sensor data. The state graph represents the set of objects and the set of positions of the set of objects. The state graph includes a set of object nodes to represent the set of objects and a set of property nodes to represent the set of properties of the set of objects. The state graph is provided to a graph enhancement module that updates the state graph with additional data to generate an enhanced state graph.

Interacting with machines using natural language input and a state graph

A method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes generating a state graph based on the sensor data. The state graph includes a set of object nodes and a set of property nodes. The method further includes obtaining user input data generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes generating a set of instructions for a set of mechanical systems based on the enhanced state graph. The method further includes operating the set of mechanical systems to achieve a set of objectives based on the set of instructions.

System for interacting with machines using natural language input

Systems and methods described receive a request for a transportation plan for a user, wherein the request comprises a starting point and an ending point for a route. Systems and methods then generate a set of potential transportation plans for the route, determine an impact of a subset of plans in the set of potential transportation plans and estimate a likelihood of acceptance of the subset of plans in the set of potential transportation plans based on a personal preference model for the user. Systems and methods also select an influence strategy of the user based on a user model and generate a message recommending a selected plan from the subset of plans for the user, wherein the message is generated based on the selected influence strategy.

User behavior influence in transportation systems

A method is provided. The method includes obtaining an enhanced state graph. The enhanced state graph represents a set of objects within an environment and a set of positions of the set of objects. The enhanced state graph includes a set of object nodes, a set of property nodes and a set of goal nodes to represent a set of objectives. The method also includes generating a set of instructions for a set of mechanical systems based on the enhanced state graph. The set of mechanical systems is configured to interact with one or more of the set of objects within the environment. The method further includes operating the set of mechanical systems to achieve the set of objectives based on the set of instructions.

Controlling mechanical systems based on natural language input

Systems and methods described receive a request for a transportation plan for a user, wherein the request comprises a starting point and an ending point for a route and generate a set of potential transportation plans for the route. The systems and methods determine an estimated travel time and an estimated fuel consumption for at least a first subset of plans in the set of potential transportation plans and estimate an impact on a transportation system of at least a second subset of plans in the set of potential transportation plans. Based at least in part on the estimated time, the estimated fuel, and the estimated impact on the transportation system, a plan is selected.

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Palo Alto, CA, United States of America

Shiwali Mohan