The use of self-powered, autonomous vehicles in agricultural and other domestic applications is provided. The vehicles include a self-propelled drive system, tracks or wheels operatively connected to the drive system, a power supply operatively connected to the drive system, an attachment mechanism for attaching equipment to the vehicle, and an intelligent control operatively connected to the drive system, power supply, and attachment mechanism. The vehicle is configured to connect to the equipment to perform agricultural operations based upon the equipment. Multiple vehicles can be used in a field at the same time. Furthermore, the invention includes the ability to move one or more of the autonomous vehicles from field to field, home to field, or from generally any first location to a second location.

A method for delimiting and monitoring at least one working area for at least one autonomously operated vehicle includes transmitting, by a transmitter and receiver unit, an output signal through a signal loop. The transmitter and receiver unit is arranged outside the vehicle and is connected using signaling technology to the signal loop. The method further includes comparing the transmitted output signal with an input signal received from the signal loop, determining, by the transmitter and receiver unit, a malfunction of the signal loop in response to a deviation between the output signal and the input signal, and initiating a securing sequence for the autonomous driving operation of the at least one vehicle.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Systems and methods are disclosed herein for displaying images of certain surroundings of an agricultural implement, for example one including a frame extending between opposing distal ends of a length transverse to a working direction of the agricultural implement. Individual image regions of the surroundings of the agricultural implement are captured using cameras arranged on the agricultural implement and directed toward a working area in the working direction, wherein a corresponding display is generated on a user interface. One or more traveling conditions (e.g., an edge of the working area and/or an edge of the frame, respectively corresponding to a first end and/or second end of the frame) may be automatically projected in the working direction, wherein respective indicia corresponding to the projected traveling conditions are superimposed on the generated display. The indicia may optionally be modified dynamically based on determined changes in a projected course of the working direction.

An illustrative modular smart implement for precision agriculture includes a chassis having a hydraulic system, a control system, and articulating tool arms that are adapted to releasably receive one of a tool attachment for working a crop and/or field, including precision planting, cultivating, thinning, spraying, harvesting, and/or data collection. A toolbar fixed to the chassis receives and supports the articulating tools arms. An alignment member and side shift actuator provide movement of a portion of the tool arms along an axis parallel to a longitudinal axis of the toolbar, and a lift actuator provide movement along a vertical axis.

A coupling device includes: a first connector that connects to a work vehicle; a second connector that connects to a work device; an actuator that changes a connecting position of at least one of the first connector and the second connector; and a control device that controls the actuator.

A work machine includes: a work vehicle; a work device coupled to the work vehicle; a control device that executes at least one of: a first control to control the work device based on a first command from the work vehicle; and a second control to control the work vehicle based on a second command from the work device; and a switching device that switches the control device between the first control and the second control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, receiving data representing a policy specifying a type of action for an agricultural object, selecting an emitter with which to perform a type of action for the agricultural object as one of one or more classified subsets, and configuring the agricultural projectile delivery system to activate an emitter to propel an agricultural projectile to intercept the agricultural object.