Abstract: Systems and methods disclosed herein provide probabilistic decision support regarding detected obstacles in a working area. Real-time data sets are collected from obstacle sensors associated with at least one self-propelled work vehicle, corresponding to detected presence/absence of obstacles at given locations within the working area. The received real-time data sets are integrated in data storage comprising a priori data sets corresponding to the working area, to generate one or more new a priori data sets. Probabilities are determined for the detected presence or absence of the obstacle, and for each of one or more obstacle categories, based on the received real-time data set and at least an a priori data set corresponding to the work vehicle's location. An output corresponding to at least a most likely of the determined probabilities is generated as feedback to a user interface, and/or relevant machine control units.

Abstract: Systems and methods disclosed herein provide probabilistic decision support regarding detected obstacles in a working area. Real-time data sets are collected from obstacle sensors associated with at least one self-propelled work vehicle, corresponding to detected presence/absence of obstacles at given locations within the working area. The received real-time data sets are integrated in data storage comprising a priori data sets corresponding to the working area, to generate one or more new a priori data sets. Probabilities are determined for the detected presence or absence of the obstacle, and for each of one or more obstacle categories, based on the received real-time data set and at least an a priori data set corresponding to the work vehicle's location. An output corresponding to at least a most likely of the determined probabilities is generated as feedback to a user interface, and/or relevant machine control units.

Abstract: An issue is detected in the operation of a mobile machine. A user interaction system is triggered, and identifies an issue-specific process based on the detected issue. Information is surfaced for an operator to perform actions to address the issue. The actions are grouped based on whether they can be performed inside or outside an operator compartment.

Abstract: A control system and method for automatically determining characteristic for optimum machine performance including a user interface console, a processor and a controller. Data for operation setting and optimization condition is fed into the control system through the user interface console. The processor processes the data by incrementing at least one variable parameter to generate an output data corresponding to each incremented variable parameter.

Abstract: A control system and method for automatically determining characteristic for optimum machine performance including a user interface console, a processor and a controller. Data for operation setting and optimization condition is fed into the control system through the user interface console. The processor processes the data by incrementing at least one variable parameter to generate an output data corresponding to each incremented variable parameter.

Abstract: An issue is detected in the operation of a mobile machine. A user interaction system is triggered, and identifies an issue-specific process based on the detected issue. Information is surfaced for an operator to perform actions to address the issue. The actions are grouped based on whether they can be performed inside or outside an operator compartment.

Abstract: Radio frequency identification tags are spaced apart from one another in or around a work area for the vehicle. Each of the tags has a corresponding unique identifier. A path planning module establishes a path comprising a path segment between at least two of the radio frequency identification tags. The path segment comprises at least one of a distance between the tags, an angular heading between the tags, and unique identifiers corresponding to the tags. A data processor determines an estimated position of the vehicle based on at least one of odometer data and accelerometer data. A vehicle controller navigates between at least two of the radio frequency identification tags based on the estimated position, the distance and the angular heading. A reader reads the tag identifiers of each tag to track the progress of the vehicle to facilitate execution of or retrieval of any next path segment of the vehicle along the established path.

Abstract: Radio frequency identification tags are spaced apart from one another in or around a work area for the vehicle. Each of the tags has a corresponding unique identifier. A path planning module establishes a path comprising a path segment between at least two of the radio frequency identification tags. The path segment comprises at least one of a distance between the tags, an angular heading between the tags, and unique identifiers corresponding to the tags. A data processor determines an estimated position of the vehicle based on at least one of odometer data and accelerometer data. A vehicle controller navigates between at least two of the radio frequency identification tags based on the estimated position, the distance and the angular heading. A reader reads the tag identifiers of each tag to track the progress of the vehicle to facilitate execution of or retrieval of any next path segment of the vehicle along the established path.