G06V20/13

IMPLEMENT MANAGEMENT SYSTEM FOR IMPLEMENT WEAR DETECTION AND ESTIMATION
20220406104 · 2022-12-22 ·

An implement management system detects implement wear and monitors implement states to modify operating modes of a vehicle. The system can determine implement wear using the pull of the implement on the vehicle, the force and angle of which is represented by an orientation vector. The system may measure a current orientation vector and determine an expected orientation vector using sensors and a model (e.g., a machine learned model). Additionally, the implement management system can determine an implement state based on images of the soil and the implement captured by a camera onboard the vehicle during operation. The system may apply different models to the images to determine a likely state of the implement. The difference between the expected and current orientation vectors or the determined implement state may be used to determine whether and how the vehicle's operating mode should be modified.

IMPLEMENT MANAGEMENT SYSTEM FOR DETERMINING IMPLEMENT STATE

An implement management system detects implement wear and monitors implement states to modify operating modes of a vehicle. The system can determine implement wear using the pull of the implement on the vehicle, the force and angle of which is represented by an orientation vector. The system may measure a current orientation vector and determine an expected orientation vector using sensors and a model (e.g., a machine learned model). Additionally, the implement management system can determine an implement state based on images of the soil and the implement captured by a camera onboard the vehicle during operation. The system may apply different models to the images to determine a likely state of the implement. The difference between the expected and current orientation vectors or the determined implement state may be used to determine whether and how the vehicle's operating mode should be modified.

ROADWAY OCCLUSION DETECTION AND REASONING

A method for updating a map including receiving a first image depicting a geographical area including a first roadway and an occluded area, determining a location of the first roadway segment in response to the first image, receiving a plurality of vehicle telemetry data associated with the first roadway segment and a second roadway segment within the occluded area, updating a map data with the location of the first roadway, determining a location of the occluded area in response to the first image and the plurality of vehicle telemetry data associated with the second roadway segment, requesting an alternate data in response to determination of the location of the occluded area, determining a location of a second roadway segment in response to the alternate data wherein the second roadway segment was occluded in the first image, and updating the map data with the location of the second roadway segment.

ABSOLUTE GEOSPATIAL ACCURACY MODEL FOR REMOTE SENSING WITHOUT SURVEYED CONTROL POINTS

Estimating absolute geospatial accuracy in input images without the use of surveyed control points is disclosed. For example, the absolute geospatial accuracy of a satellite images may be estimated without the use of control points (GCPs). The absolute geospatial accuracy of the input images may be estimated based on a statistical measure of relative accuracies between pairs of overlapping images. The estimation of the absolute geospatial accuracy may include determining a root mean square error of the relative accuracies between pairs of overlapping images. For example, the absolute geospatial accuracy of the input images may be estimated by determining a root mean square error of the shears of respective pairs of overlapping images. The estimated absolute geospatial accuracy may be used to curate GCPs, evaluate a digital elevation map, generate a heatmap, or determine whether the adjust the images until a target absolute geospatial accuracy is met.

LAND MANAGEMENT AND RESTORATION

Provided herein are systems and methods for identifying a recommended treatment to land. An example method comprises: identifying a plurality of sites of interest in the land; segmenting the land into a plurality of areas based on ownership information and ecological information; identifying, for a particular area of the plurality of areas, a plurality of potential treatments; calculating a performance metric for each of the plurality of potential treatments to obtain a plurality of performance metrics for the particular area, wherein each performance metric of the plurality of performance metrics is calculated based on one or more sites of interest located in the particular area; and selecting the recommended treatment for the particular area of the land from the plurality of potential treatments based on the plurality of performance metrics.

LAND MANAGEMENT AND RESTORATION

Provided herein are systems and methods for identifying a recommended treatment to land. An example method comprises: identifying a plurality of sites of interest in the land; segmenting the land into a plurality of areas based on ownership information and ecological information; identifying, for a particular area of the plurality of areas, a plurality of potential treatments; calculating a performance metric for each of the plurality of potential treatments to obtain a plurality of performance metrics for the particular area, wherein each performance metric of the plurality of performance metrics is calculated based on one or more sites of interest located in the particular area; and selecting the recommended treatment for the particular area of the land from the plurality of potential treatments based on the plurality of performance metrics.

SYSTEMS AND METHODS FOR CALCULATING WATER RESOURCES USING AERIAL IMAGING OF CROP LANDS
20220406055 · 2022-12-22 ·

Systems and methods for determining groundwater levels based upon crop classification are provided. A set of aerial images are collected via satellite, manned aircraft or drones. They are filtered by a time domain, and a sufficiently high-resolution image is selected. If there isn't an image with sufficient resolution, a series of lower resolution images may be combined to generate a ‘fused’ image suitable for analysis. The image is then subjected to pre-processing. Crop boundaries within the image are determined, and areas outside of the crop boundary are masked off. The resulting image is subjected to a sliding window algorithm to generate discrete “patches” of the image suitable for analysis by a trained neural network. The neural network generated a classification for the crop. This data may be combined with surface water data, precipitation data, and weather pattern data to determine groundwater levels.

REMOTE SENSING OF TERRAIN STRENGTH FOR MOBILITY MODELING

Methods for characterizing soil stiffness of an area. One example method includes receiving, with an electronic processor, a parameter corresponding to a soil type of the area; receiving, with the electronic processor, a plurality of thermal images of the area; determining, with the electronic processor, an apparent thermal inertia of the area based on the plurality of thermal images; determining, with the electronic processor, a soil gradation of the area based on the parameter; determining, with a machine learning algorithm executed by the electronic processor, an approximate soil stiffness of the area based on the apparent thermal inertia; and outputting, to a display communicatively coupled to the electronic processor, a representation of the approximate soil stiffness.

METHOD AND SYSTEM FOR PLANNING VEHICLE TRAJECTORIES BY ENHANCING EN ROUTE NAVIGATION PERFORMANCE

A method for planning a vehicle trajectory is provided. The method comprises obtaining an edge map representation corresponding to one or more terrain images of a given area, and identifying a total number of edge pixels in each of a plurality of sub-regions of the edge map representation. The method further comprises determining a measurement probability density function (PDF) for each of the sub-regions based on the number of edge pixels with information content in each sub-region. The method then computes a trajectory cost for each of the sub-regions by dividing a user-selected scalar by a sum of: a user-selected value and the number of edge pixels with information content in each sub-region. Thereafter, the method selects a trajectory for navigation of a vehicle over the given area based on the trajectory cost for each of the sub-regions.

Remote Control Device with Environment Mapping
20220405317 · 2022-12-22 ·

A remote control device for controlling devices in an environment can utilize an environment map and location information to accurately determine an intended device to provide control for multiple devices in an environment. The environment mapping can be performed using the remote control device including a plurality of sensors. A spatial map can be generated for an environment along with location information for controllable devices within the environment. The spatial map and location information can be stored on the remote control device. The mapping can allow the remote control device to quickly group devices or drag and drop content from one type of device to another type of device. The remote control device can perform search queries based on combinations of image and audio data in some examples.