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.

A response system may be provided. The response system may include a security system and an autonomous drone. The security system includes a security sensor and a controller. The drone includes a processor, a memory in communication with the processor, and a drone sensor. The processor may be programmed to receive the deployment request from the security system, navigate to the one or more zones of the coverage area included in the deployment request, collect drone sensor data of the one or more zones of the coverage area using the at least one drone sensor, determine that an incident has occurred, and/or transmit the collected drone sensor data and incident verification to the security system, wherein, in response to receiving the collected drone sensor data and incident verification, the security system is configured to generate a command for responding to the incident.

A power generation system for wheeled objects comprises a generator mechanically coupled to one or more of the object's wheels to convert wheel rotational energy into electrical energy. The power generation system may comprise an electrical storage device configured to store the electrical power produced by the generator. Power from the generator and/or the electrical storage device can be used to provide power to other electrical systems in or on the object. In certain embodiments, the electrical storage device comprises a bank of high-capacity capacitors connected in series. Some embodiments use a control circuit, for example, to regulate the charging and discharging of the capacitor bank and to provide suitable voltages for other systems. The power generation system may be disposed within an object's wheel, such as a wheel of a shopping cart.

Systems, methods, and computer-readable media are disclosed for improved smart infrastructure data transfer. An example method may involve receiving, by a smart infrastructure device and from a first vehicle, first information associated with the first vehicle in a first format associated with a first communication protocol. The first information is converted from the first format into an agnostic format. An image, video, or real-time feed of an environment of the smart infrastructure device is captured. The first vehicle and a second vehicle in the image, video, or real-time feed is identified. It is determined that the second vehicle is temporarily or permanently incapable of performing a communication with the smart infrastructure device based on the image, video, or real-time feed. The image, video, or real-time feed is analyzed to generate second information associated with the second vehicle. The second information is converted into the agnostic format.

Techniques are disclosed for collaborative map construction using multiple vehicles. Such a system may include a ground vehicle including a first computing device and a first scanning sensor, and an aerial vehicle including a second computing device and a second scanning sensor. The ground vehicle can obtain a first real-time map based on first scanning data using the first scanning sensor, and transmit a first real-time map and position information to the aerial vehicle. The aerial vehicle can receive the first real-time map and the position information from the first computing device, obtain a second real-time map based on second scanning data collected using the second scanning sensor, and obtain a third real-time map based on the first real-time map and the second real-time map.

Example navigation aids for increasing the accuracy of a navigation system are disclosed herein. An example method disclosed herein identifying, with an aircraft intent description language (AIDL) aid, an AIDL instruction as associated with a first dynamic activity level of a plurality of dynamic activity levels and determining, with the AIDL aid, an aircraft state to be affected by the AIDL instruction. The example method also includes changing, with a navigation filter, a weighting scheme for a measurement of the aircraft state obtained by an inertial navigation system (INS) of the aircraft and estimating, with the navigation filter, a trajectory of the aircraft based on the weighting scheme and the measurement.

A system, a method and instructions embodied on a non-transitory computer-readable storage medium that solve a 3D point-in-polygon (PIP) problem is presented. This system projects polygons that comprise a set of polyhedra onto projected polygons in a reference plane. Next, the system projects a data point onto the reference plane, and performs a 2D PIP operation in the reference plane to determine which projected polygons the projected data point falls into. For each projected polygon the projected data point falls into, the system performs a 3D crossing number operation by counting intersections between a ray projected from the corresponding data point in a direction orthogonal to the reference plane and polyhedral faces corresponding to projected polygons, to identify polyhedra the data point falls into. The system then generates a visual representation of the set of polyhedra, wherein each polyhedron is affected by data points that fall into it.

A system, a method and a device for planning a driving path for a vehicle are described. In one example aspect, the device is configured to: analyze sense data to obtain positioning data of vehicles; assign vehicle transportation tasks to an unmanned vehicle and a manned vehicle in the predetermined area in accordance with a predetermined transportation task, each vehicle transportation task including a transportation start point and a transportation end point; plan driving paths for the unmanned vehicle and the manned vehicle based on the assigned vehicle transportation tasks, the vehicle positioning data and map data; transmit the assigned transportation task and the planned driving path for the unmanned vehicle to the unmanned vehicle; and transmit the assigned transportation task and the planned driving path for the manned vehicle to a mobile device corresponding to the manned vehicle.

A computer-implemented method for controlling a vehicle comprises: receiving tracking data associated with a surrounding environment of the vehicle; detecting, based upon the tracking data, an object in the surrounding environment of the vehicle; determining a location of the object; determining, based on navigation assistance data, whether the location of the object is at least partially within a classified area in the surrounding environment; and configuring a control system of the vehicle to: initiate, based upon determining that the location of the object is not at least partially within the classified area, a first collision avoidance response procedure for responding to the object; and initiate, based upon determining that the location of the object is at least partially within the classified area, a second collision avoidance response procedure for responding to the object, the second collision avoidance response procedure different from the first collision avoidance response procedure.