A system and method are provided for evenly distributing the loading of material in a loading container of a transport vehicle (e.g., articulated dump truck) by a work machine (e.g., excavator). At least one sensor mounted on the work machine generates data corresponding to at least a portion of the loading container. The captured data is processed to determine a current profile of material loaded in the loading container, wherein output signals are generated corresponding to a difference between the current profile and a predetermined target profile for the material loaded in the loading container. In certain embodiments, the output signals are used to assist an operator of the work machine with manual loading via an onboard display unit and superposed images associated with the current and/or target profiles. In other embodiments, the output signals automatically control at least part of the loading process.

A system and method are provided for flow synchronization between various transport vehicles (e.g. dump trucks) and a work machine (e.g. excavator) in a material loading cycle. The work machine and each transport vehicle are configured to communicate with each other via a machine-to-machine communications network. A controller determines initiation of a loading cycle associated with the work machine and a first transport vehicle, and detects certain parameters corresponding to a duration of the loading cycle (e.g. weight of payload, volume of truck bin, historical cycle data). A remaining time in the loading cycle duration is accordingly estimated, and an output signal corresponding to the estimated remaining time is generated to at least a next transport vehicle in a loading sequence. The system and method facilitate even spacing of transport vehicles, consistent travel speeds, and optimization of a number of loading vehicles required to coordinate with a given work machine.

A system for removing carryback material from within a dump body of a haul truck includes a clean out implement. A controller is configured to determine the pose of the dump body, determine the pose of the clean out implement, determine a path of the clean out implement to remove carryback material from the interior surface of the dump body based upon a map of the carryback material, the pose of the dump body, and the pose of the clean out implement, and generate movement command signals to move the clean out implement along the path to perform a clean out operation on the interior surface of the dump body.

A measuring arrangement includes a positioning arrangement including at least one locator, at least one first spot to be located, at least one second spot to be located, and a position data gathering unit for gathering a first set of at least three different position data measurements of each of the at least one first spot to be located, wherein the different position data measurements are taken in different rotation angles around a first axle, and a second set of at least three different position data measurements of each of the at least one second spot to be located, wherein the different position data measurements are taken in different rotation angles around a second axle. The three dimensional location and orientation of the center axis of the first axle with respect to the center axis of the second axle are determined on the basis of the first and second set of position data measurements.

In accordance with an example embodiment, a method for directing a work machine to one or more worksites from a selection of candidate worksites is disclosed. The method includes receiving obscurant data related to a forecast availability of obscurants at one or more worksites; receiving environmental data related to the suppression, creation, transportation, or direction of obscurants; and receiving operational data related to machine components and the ability of the machine components to generate obscurants or have performance degraded by obscurants at the one or more worksites. Determining an obscurant metric for each of the one or more worksites based on the obscurant data, the environmental data, and the operational data; and directing the work machine to the one or more worksites based on the obscurant metric.

A worksite classification system and method for classifying persons at a worksite is disclosed. The worksite classification system can include a sensor system configured to capture images of persons located at the worksite. An electronic data processor communicatively coupled to the sensor system and comprising a computer readable storage medium having machine readable instructions that, when executed by the electronic data processor, cause the processor to: determine an identity of the persons based on one or more identifying characteristics associated with the persons; determine if the persons have authorization access to enter to one or more operational zones at the worksite based on the identity of the persons and an associated access level; and generate an alert notifying an operator when persons without authorization access enters the one or more operational zones.

In embodiments, a work vehicle magnetorheological fluid (MRF) joystick system includes a joystick device, an MRF joystick resistance mechanism, and a controller architecture. The joystick device includes, in turn, a base housing, a joystick, and a joystick position sensor. The MRF joystick resistance mechanism is controllable to selectively resist movement of the joystick relative to the base housing. The controller architecture is configured to: (i) when detecting operator rotation of the joystick in an operator input direction, determine whether continued joystick rotation in the operator input direction will misposition the work vehicle in a manner increasing at least one of work vehicle instability and a likelihood of work vehicle collision; and (ii) when determining that continued joystick rotation will misposition the work vehicle, command the MRF joystick resistance mechanism to generate an MRF resistance force deterring continued joystick rotation in the operator input direction.

A shovel includes a lower traveling body, an upper turning body mounted on the lower traveling body; and a receiver, a direction detecting device, a controller, and a display device mounted on the upper turning body, wherein the receiver is configured to receive an image captured by a camera-mounted autonomous aerial vehicle, the direction detecting device is configured to detect a direction of the shovel, the controller is configured to generate information related to a target rotation angle of the camera-mounted autonomous aerial vehicle based on the direction of the shovel, and the display device is configured to display the captured image in a same direction as a direction of an image that is captured when the camera-mounted autonomous aerial vehicle rotates by the target rotation angle.

A shovel includes a lower traveling body, an upper turning body, an attachment including a boom, an arm, and an end attachment, a boom state detector configured to detect the state of the boom, an arm state detector configured to detect the state of the arm, an end attachment state detector configured to detect the state of the end attachment, and a hardware processor. The hardware processor is configured to obtain information on the position of the end attachment based on the respective outputs of the detectors, correlate the information on the position of the end attachment with information on the position of an underground object obtained based on the output of an underground object detector, and calculate the distance between the end attachment and the underground object. The hardware processor is further configured to control the shovel such that the distance is prevented from falling below a predetermined value.

The present disclosure relates generally to the operation of autonomous machinery for performing various tasks at various industrial work sites, and more particularly to the volumetric estimation and dimensional estimation of a pile of material or other object, and the use of multiple sensors for the volumetric estimation and dimensional estimation of a pile of material or other object at such work sites. An application and a framework is disclosed for volumetric estimation and dimensional estimation of a pile of material or other object using at least one sensor, preferably a plurality of sensors, on an autonomous machine (e.g., robotic machines or autonomous vehicles) in various work-site environments applicable to various industries such as, construction, mining, manufacturing, warehousing, logistics, sorting, packaging, agriculture, etc.