Caterpillar Inc.

Stefan Jacob Wulf

Cameron T Lane

Jason Bell

Andrew Seungyul Yun

Justin Lee Steinlage

Darryl Victor Collins

Christopher M Sprock

Thomas Frank Doherty

Mahmoud M Tobaa

Mallikharjuna Rao Boddu

Daryl R Brower

Greg Davis

Systems and methods are disclosed for managing task assignments for a fleet of haul trucks at a mine site. An assignment engine may: receive state data for a haul truck including haul weight data and second state data for the mine site that is indicative of a plurality of available tasks and associated task material weight data; assign a task to the haul truck by inputting the state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function, such that the learned policy accounts for vehicle performance variance due to changing vehicle haul weight and/or road conditions; and cause the at least one haul truck to be operated according to the at least one task assignment.

Systems and methods for managing assignments of tasks for mining equipment using machine learning

Systems and methods are disclosed for managing task assignments for a plurality of work machines at a site. An assignment engine may: receive first state data for a work machine including historical data, operating condition, and location data, and second state data for the site including characteristic data for materials and a plurality of available tasks; predict performance data and energy consumption data of the work machine for a task; select a task for the work machine by inputting first state data and second state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function such that the learned policy selects a task for at least one work machine from the plurality of tasks available at the site; and cause the at least one work machine to be operated according to the at least one task assignment.

Systems and methods for managing assignments of tasks for work machines using machine learning

A method for detecting an unbalanced payload condition in a machine is disclosed. The method includes detecting, by a first sensor, a pressure exerted on each of one or more struts in the machine by a payload. The method further includes detecting, by a second sensor, one or more operational parameters associated with machine. Furthermore, method includes determining, by a controller, a center of gravity of the payload based on detected pressure, the one or more operational parameters, and one or more dimensions of the machine. Additionally, the method includes determining, by the controller, a force being exerted, by the payload, on each traction member of the machine based on the center of gravity of the payload. The method further includes detecting, by the controller, the unbalanced payload condition when the force, being exerted on at least one traction member of the plurality of traction members, exceeds a threshold value.

Methods and systems for detecting unbalanced payload condition in machines

A method of operating a machine at a worksite includes determining data associated with at least one of a machine operation at the worksite and a worksite condition, and determining, based on the data, that one of machine propulsion and machine retarding will be required for greater than a corresponding threshold. The method also includes determining, in response to determining that machine propulsion will be required, a desired propulsion gear, and recommending the propulsion gear to an operator of the machine. The method further includes determining, in response to determining that machine retarding will be required, a desired retarding gear, and recommending the retarding gear to the operator. In such a method, the retarding gear is determined based on a maximum temperature associated with the machine.

Worksite management system with gear recommendation

A method and system for managing cruise control in a machine provide for maintaining a speed of the machine at a target speed in the absence of an acceleration or deceleration command from an operator of the machine. When a deceleration command is received from the operator of the machine the machine is slowed below the target speed while the deceleration command is received and is returned to the target speed when the deceleration command is no longer received.

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Washington, IL, United States of America

Stefan Jacob Wulf