An approach is disclosed for estimating population density change where dynamic signals are not available or are not dense enough to be representative. The approach involves, for example, determining map features of a first map space. The approach also involves identifying partitions of the first map space based on the identified partitions (i) having features that are substantially similar, and (ii) having respective change functions that are substantially similar. The approach further involves determining an estimated change function based on one or more of the respective change functions that are substantially similar and that are associated with the first map space. The approach further involves using the estimated change function for at least one partition of a second map space based on the at least one partition of the second map space and at least one map partition of the first map space having map features that are substantially similar.

A mobile agricultural machine obtains an agricultural characteristic map indicative of agricultural characteristics of a field, wherein the agricultural characteristic map is based on data collected at or prior to a first time. The mobile agricultural machine obtains supplemental data indicative of characteristics relative to the worksite, the supplemental data collected after the first time. An agricultural characteristic confidence output, indicative of a confidence level in the agricultural characteristics indicated by the agricultural characteristic map, is generated based on the agricultural characteristic map and the supplemental data. In some examples, an action signal is generated to control an action of the mobile agricultural machine based on the agricultural characteristic confidence output.

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 method for occupancy map synchronization in multi-vehicle networks may include receiving three-dimensional perception sensor (3DPS) data. The method may include generating a data message including an occupancy map (OM) octree. The OM octree may be generated from an occupancy map constructed from the 3DPS data. The method may include reducing at least one of a messaging time or a messaging size of the data message including the OM octree. The method may include transmitting the data message including the OM octree via a leader vehicle controller communicatively coupled to a leader vehicle. The method may include receiving the data message comprising the OM octree via a follower vehicle controller communicatively coupled to the follower vehicle. The method may include generating a local occupancy map from the data message comprising the OM octree via the follower vehicle controller.

An imaging system can include a first and second camera configured to capture first and second sets of oblique images along first and second scan paths, respectively, on an object area. A drive is coupled to a scanning mirror structure, having at least one mirror surface, and configured to rotate the structure about a scan axis based on a scan angle. The first and second cameras each have an optical axis set at an oblique angle to the scan axis and include a respective lens to focus first and second imaging beams reflected from the mirror surface to an image sensor located in each of the cameras. The first and second imaging beams captured by their respective cameras can vary according to the scan angle. Each of the image sensors captures respective sets of oblique images by sampling the imaging beams at first and second values of the scan angle.

According to one aspect, an information processing apparatus includes: a terrain data processing unit which performs a terrain data process of calculating a terrain coordinate group based on terrain data in which a position and a shape of an object are represented by a plurality of nodes or are represented by a plurality of nodes and a link between the nodes; and a selection processing unit which selects nodes adjacent or close to each other, indicated by the terrain coordinate group calculated by the terrain data processing unit, and selects a node suitable to calculate a width of the object from other nodes based on a positional relationship between the selected nodes and the other nodes.

A soil measure, such as a soil cone index, and a vehicle index indicating the amount of force the vehicle exerts on the ground as it travels over the ground, are obtained and compared to identify a soil damage score. The soil damage score can be mapped over a field and an agricultural vehicle can be controlled based upon the soil damage score.

A method and system for zone mapping displays a geographic area to a user and receives input from the user identifying a zone of the geographic area. An identification of an agricultural material to be applied in the zone is also received and an application plan is generated in response. The application plan is generated based on features identified in the zone, the agricultural material to be applied, and application requirements and restrictions associated with the agricultural material that are identified by the manufacturer of the material and, in some cases, governmental agencies. The agricultural machine tracks the application of the agricultural material and transmits application information for storage in the zone mapping system for later retrieval in response to requests, such as compliance requests.

Methods and systems are provided herein for a dust box cleanout routine of an evaporative emissions control (EVAP) system of a vehicle. In one example, a method is provided for an engine of a vehicle, comprising, during travel on an unpaved road, selectively discharging a dust box housed in a vent line of an evaporative emissions control (EVAP) system by opening a discharge valve of the dust box leading to atmosphere. In this way, an accumulation of dust on the air filter and in the dust box of the EVAP system may be reduced, thereby maintaining an efficiency of the EVAP system.

An apparatus, method and computer program product are provided for predicting charging efficiency rates for solar-powered vehicles. In one example, the apparatus receives historical data of events in which solar-powered vehicles equipped with solar panels were electrically charged by receiving solar beams at the solar panels. The historical data indicate factors of the events that induced objects forming on the solar panels and obstructing, at least in part, the solar beams. The apparatus uses the historical data to train a machine learning model to output a charging efficiency rate of a target solar-powered vehicle as a function of at least one attribute associated with a location.