This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collects any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

A control device that controls a work vehicle including work equipment includes: a route acquisition unit that acquires a traveling route of a transport vehicle; an area setting unit that sets a limit area for limiting entry of the work equipment along the traveling route; and a signal output unit that outputs a signal for controlling the work vehicle or the transport vehicle on the basis of a relationship between the limit area and the work equipment.

A work vehicle includes a work implement. A control system for the work vehicle includes a controller. The controller acquires work range data indicative of a work range. The controller determines a division distance by dividing an entire length of the work range by a predetermined number of divisions. The controller determines a plurality of starting positions so that the distance between each starting position matches the division distance in the work range. The controller generates an instruction signal to actuate the work implement from the plurality of starting positions.

A system of this disclosure includes an artificial intelligence module, which may include a neural network or a decision tree architecture, configured to analyze data indicative of the manner in which an operator performs tasks using a heavy machine. The artificial intelligence module is further configured to provide instructions pertaining to the control of at least some components of the heavy machine. As such, the heavy machine is operated in whole or in part based on the direction of the artificial intelligence module, which reduces reliance on a human operator. The artificial intelligence module is highly efficient, and in particular the artificial intelligence module is trained relatively quickly. Further, the artificial intelligence module may be embodied on the heavy machinery itself, as opposed to on a cloud-based system or on a more high-powered computer. Accordingly, the cost of implementing and operating the disclosed system is relatively low.

A visual reference system can be used with a loading machine such as a bucket loader having a bucket that can be vertically articulated with respect to a work surface. The visual reference system can include one or more illumination devices configured to project a visual fiducial beam toward the work surface. The visual fiducial beam can create a fiducial indication of where the bucket will contact the work surface when lowered adjacent the work surface. The visual reference system can assist in operation of the loading machine by enabling an operator to visually perceive the expected contact point between the bucket and work surface.

A work machine, such as a wheel loader, operating in a worksite within a wireless control system includes an operator-specific configuration of machine settings associated with an identification for the operator. As the work machine executes a work function, the operator identification, an initial operator-specific configuration, and sensed performance metrics are transmitted to a control system for the worksite. Linking the operator identification to one or both of the initial operator-specific configuration and the metrics, the control system analyzes performance of the work machine by the operator with increased granularity and flags potential irregularities. A modified operator-specific configuration to change operator performance is returned to the work machine and made to override the initial operator-specific configuration when the operator next takes control of the work machine.

Methods, systems, and apparatus are described herein for providing operational efficiency at a construction site through a connected system of on-board mobile computers.

A system for autonomous or semi-autonomous operation of a vehicle is disclosed. The system includes a machine automation portal (MAP) application configured to enable a computing device to (a) display a map of a work site and (b) provide a graphical user interface that enables a user to (i) define a boundary of an autonomous operating zone on the map and (ii) define a boundary of one or more exclusion zones. The system also includes a robotics processing unit configured to (a) receive the boundary of the autonomous operating zone and the boundary of each exclusion zone from the computing device, (b) generate a planned command path that the vehicle will travel to perform a task within the autonomous operating zone while avoiding each exclusion zone, and (c) control operation of the vehicle so that the vehicle travels the planned command path to perform the task.

A self-propelled work vehicle is provided with a control system enabling the use of gestures on a touch screen interface to provide a simple and intuitive way to manipulate displayed images, and/or automatically changing a region of interest of a surround view camera unit. Exemplary automatic manipulation may be implemented if a work vehicle is detected as performing a certain function, wherein surround view images can automatically change to a smaller sub-view which gives more focused visibility appropriate to that function. The distortion and simulated field of view of surround view images may also/otherwise be automatically manipulated based on a detected operation/function. The control system can also/otherwise dynamically modify surround view images in accordance with a detected work state, and/or based on outputs from an obstacle detection system. The control system can also/otherwise lock the sub-view to recognized objects of interest, such as trucks or trenches.

A self-propelled construction machine for milling a ground surface is provided with a machine frame, a working drum, and a transport conveyor with a discharge end from which worked-off milling material is dischargeable onto a point of impingement on a loading surface of a transport vehicle, wherein the transport conveyor is laterally slewable to a slewing angle about at least a first slewing axis. A controller is configured, during an initialization process, to specify a command variable within a coordinate system independent of a position and/or orientation of the machine, the coordinate system being stored during the initialization process with its origin at a starting point associated with the machine. The controller is further configured during a working process, wherein the coordinate system is stationary, to automatically control the slewing angle corresponding to detected changes in position and/or orientation of the machine and relative to the command variable.