A system and method for electronically assessing operator performance when operating a working machine adapted to handle or process ground material. The system and method can identify compliance with operating instructions for operating the working machine and/or can uniquely characterize functions of the working machine based on external factors.

Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles (e.g., construction and/or mining vehicles), including to automatically determine and control movement around a site. For example, the systems/techniques may determine and implement autonomous operations of earth-moving vehicles by determining current location and positioning of an earth-moving vehicle on the site, determining a command for the earth-moving vehicle, and causing the earth-moving vehicle to perform the command—the autonomous operations may in some situations further include obtaining and integrating data from sensors of multiple types on the earth-moving vehicle, implementing coordinated actions of multiple earth-moving vehicles of one or more types, etc.

Systems and techniques are described for implementing autonomous control of earth-moving construction and/or mining vehicles, including to automatically determine and control autonomous movement (e.g., of a vehicle's hydraulic arm(s), tool attachment(s), tracks/wheels, rotatable chassis, etc.) to move materials or perform other actions based at least in part on data about an environment around the vehicle(s). A perception system on a vehicle that includes at least a LiDAR component may be used to repeatedly map a surrounding environment and determine a 3D point cloud with 3D data points reflecting the surrounding ground and nearby objects, with the LiDAR component mounted on a component part of the vehicle that is moved independently of the vehicle chassis to gather additional data about the environment. GPS data from receivers on the vehicle may further be used to calculate absolute locations of the 3D data points.

A management system includes a position detection unit which obtains a position of a work machine, a posture detection unit which obtains a posture of the work machine, an object detection unit which obtains a three-dimensional shape of a buried object, a position calculation unit which obtains a position of the buried object by using the position of the work machine obtained by the position detection unit, the posture of the work machine obtained by the posture detection unit, and the three-dimensional shape of the buried object obtained by the object detection unit, and an information acquisition unit which acquires buried object information including at least the position of the buried object obtained by the position calculation unit.

The present disclosure is directed to systems and methods for wear prediction of an undercarriage of a target machine. The method includes (1) receiving wear measurements from a plurality of source machines, and the wear measurements are associated with a first set of components of undercarriages of the plurality of source machines; (2) establishing a statistical model based on the received wear measurements and physic-based features derived from the wear measurements; (3) determining coefficients for the statistical model at least partially based on inspection data of a second set of components of the undercarriage of the target machine; and (4) predicting a wear condition of the undercarriage of the target machine by the statistical model and the coefficients.

A heavy-duty interactive (HDi) system may include a heavy-duty vehicle; a work tool installed on the heavy-duty vehicle; a memory that stores a plurality of patterns representing operation events for the heavy-duty vehicle; a first sensor affixed to the heavy-duty vehicle that collects first sensor data as the heavy-duty vehicle is operated; a second sensor affixed to the work tool that collects second sensor data as the work tool is operated; and a controller operatively coupled to the first sensor, the second sensor, and the memory. The controller may be configured to identify a heavy-duty vehicle operation event by comparing at least one of the first sensor data and the second sensor data with the plurality of patterns in the memory, and associate the work tool with the heavy-duty vehicle based on a comparison of the first sensor data and the second sensor data.

A method of controlling a mobile work machine on a worksite including receiving an indication of an object detected on the worksite, determining a location of the object relative to the mobile work machine, receiving an image of the worksite, correlating the determined location of the object to a portion of the image, and generating a control signal that controls a display device to display a representation of the image with a visual object indicator that represents the detected object on the portion of the image.

The present disclosure provides a fatigue management system capable of managing fatigue of each portion of a construction machine more accurately than conventional systems. The fatigue management system S includes: a stress calculation section S1 that calculates stress acting on a plurality of portions of the construction machine based on the output of a sensor 18 attached to a part of the construction machine; a damage degree calculation section S2 that calculates the cumulative damage degree of each portion of the construction machine based on the stress calculated by the stress calculation section S1; and an index value calculation section S3 that calculates a fatigue index value, which is a weighted value of the cumulative damage degree, for each portion.

A management system for an autonomous travel vehicle includes: a work machine position acquisition unit that acquires a position of a work machine operated by an operator and having a travel device; and a target position determination unit that determines a target position of the autonomous travel vehicle based on the position of the work machine.

A control system for an autonomous travel vehicle includes: a work machine position acquisition unit that acquires a position of a work machine; an autonomous travel vehicle position acquisition unit that acquires a position of the autonomous travel vehicle; a human information acquisition unit that acquires human information indicating whether or not a person is present inside the autonomous travel vehicle; and a command generation unit that changes control of the autonomous travel vehicle based on the human information and a positional relationship between the work machine and the autonomous travel vehicle.