Abstract: A method includes defining a two-dimensional geographic region by two-dimensional geographic coordinates to define the bounds of the region, converting each of the two-dimensional coordinates to three dimensional coordinates by way of a lookup stored in a computer readable medium, generating a three-dimensional grid of points, each spaced in an arrangement to encompass coverage of a predetermined ground area, and applying heuristics for a shortest path planning, relative to the three-dimensional grid of points.

Abstract: The present application relates to systems for programming devices, such as unmanned autonomous vehicles or “drones,” with a card-based format and methods for using the same. The system and methods generally comprise a programming system that receives one or more instructional cards selected by a user. The system generates an executable program based on the instructional cards received, and transmits the program to a device for execution.

Abstract: From a hardware sensor at a first time, sensor data comprising a first sample and a second sample is received. The sensor data is modified to create new data, wherein a first data point of the new data corresponds to the first sample, a second data point of the new data corresponds to the second sample, and wherein the first data point and the second data point are arranged differently from the first sample and the second sample. The hardware sensor is emulated by sending, to a consumer of hardware sensor data at a second time, the new data instead of the sensor data.

Abstract: From a hardware sensor at a first time, sensor data comprising a first sample and a second sample is received. The sensor data is modified to create new data, wherein a first data point of the new data corresponds to the first sample, a second data point of the new data corresponds to the second sample, and wherein the first data point and the second data point are arranged differently from the first sample and the second sample. The hardware sensor is emulated by sending, to a consumer of hardware sensor data at a second time, the new data instead of the sensor data.

Abstract: The present application relates to systems for programming devices, such as unmanned autonomous vehicles or “drones,” with a card-based format and methods for using the same. The system and methods generally comprise a programming system that receives one or more instructional cards selected by a user. The system generates an executable program based on the instructional cards received, and transmits the program to a device for execution.

Abstract: Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.

Abstract: The present application relates to systems for programing devices, such as unmanned autonomous vehicles or “drones,” with a card-based format and methods for using the same. The system and methods generally comprise a programing system that receives one or more instructional cards selected by a user. The system generates an executable program based on the instructional cards received, and transmits the program to a device for execution.

Abstract: Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.

Abstract: Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.

Abstract: Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.

Abstract: The present application relates to systems for programming devices, such as umanned autonomous vehicles or “drones,” with a card-based format and methods for using the same. The system and methods generally comprise a programming system that receives one or more instructional cards selected by a user. The system generates an executable program based on the instructional cards received, and transmits the program to a device for execution.

Abstract: An approach is disclosed that receives, at a wearable sensing element worn by a user, sensor data that pertains to the user's physiological functions. Physiological states pertaining to the user are calculated from the received sensor data, with the physiological states including both physical states and mental states. The calculated physiological state is matched to an environmental action states, and environmental actions are responsively performed to change a physical environment of the user.

Abstract: Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.

Abstract: Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.

Abstract: Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.

Abstract: Techniques are disclosed for identifying which graphical user interface (GUI) screens of an application that is under development would benefit from a voice user interface (VUI). A GUI screen parser analyzes to determine the GUI objects within GUI screens of the application. The parser assigns a speechability score to each analyzed GUI screen. Those GUI screens that have a higher speechability score than a predetermined speechability threshold are indicated as GUI screens that would benefit (e.g., the user experience in interacting with those GUI screens would increase, the number of GUI screens displayed would be reduced, or the like) with the addition of a VUI.

Abstract: Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.

Abstract: Techniques are disclosed for identifying which graphical user interface (GUI) screens of an application that is under development would benefit from a voice user interface (VUI). A GUI screen parser analyzes to determine the GUI objects within GUI screens of the application. The parser assigns a speechability score to each analyzed GUI screen. Those GUI screens that have a higher speechability score than a predetermined speechability threshold are indicated as GUI screens that would benefit (e.g., the user experience in interacting with those GUI screens would increase, the number of GUI screens displayed would be reduced, or the like) with the addition of a VUI.

Abstract: Techniques are disclosed for identifying which graphical user interface (GUI) screens of an application that is under development would benefit from a voice user interface (VUI). A GUI screen parser analyzes to determine the GUI objects within GUI screens of the application. The parser assigns a speechability score to each analyzed GUI screen. Those GUI screens that have a higher speechability score than a predetermined speechability threshold are indicated as GUI screens that would benefit (e.g., the user experience in interacting with those GUI screens would increase, the number of GUI screens displayed would be reduced, or the like) with the addition of a VUI.

Abstract: Techniques are disclosed for identifying which graphical user interface (GUI) screens of an application that is under development would benefit from a voice user interface (VUI). A GUI screen parser analyzes to determine the GUI objects within GUI screens of the application. The parser assigns a speechability score to each analyzed GUI screen. Those GUI screens that have a higher speechability score than a predetermined speechability threshold are indicated as GUI screens that would benefit (e.g., the user experience in interacting with those GUI screens would increase, the number of GUI screens displayed would be reduced, or the like) with the addition of a VUI.