Abstract: A vehicle row follow system may include a vehicle comprising at least one sensor to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image of a region forward the vehicle. The system may further include a non-transitory computer readable medium containing instructions to direct a processor to: determine plan row lines in a 2D image; determine a yaw of the vehicle based upon a slope of a heading line relative to a centerline between the plant row lines in the 2D image; determine a lateral offset of the vehicle from the centerline between the consecutive plant rows based upon an identity of the consecutive plant rows in the 3D point cloud; and output steering control signals based upon the determined yaw and lateral offset of the vehicle.

Abstract: An obstruction avoidance system may include a agronomy vehicle, at least one sensor configured to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image, and instructions to direct a processor to capture a particular 2D image and to obtain signals serving as a basis for a particular 3D point cloud; identify an obstruction candidate in the particular 2d image; correlate the obstruction candidate to a portion of the particular 3D point cloud to determine a value for a parameter of the obstruction candidate; classify the obstruction candidate as an obstruction based upon the parameter; and output control signals to alter a state of the agronomy vehicle in response to the obstruction candidate being classified as an obstruction.

Abstract: A plant locating system may include a vehicle supporting a Global Positioning System (GPS) antenna and a monocular camera. The system may further include a plant locating unit comprising a processing unit and a non-transitory computer-readable medium containing instructions to direct the processing unit to: acquire a sample image of a plant of interest captured at a time with the monocular camera at an unknown distance from the plant of interest (POI); determine a geographic location estimate of the GPS antenna at the time; identify a selected portion of the sample image comprising the POI; determine a distance between the POI and the monocular camera based upon the selected portion; and determine a geographic location estimate of the POI based on the geographic location estimate of the GPS antenna at the time and the determined distance between the monocular camera and the POI.

Abstract: A vehicle row follow system may include a vehicle comprising at least one sensor to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image of a region forward the vehicle. The system may further include a non-transitory computer readable medium containing instructions to direct a processor to: determine plan row lines in a 2D image; determine a yaw of the vehicle based upon a slope of a heading line relative to a centerline between the plant row lines in the 2D image; determine a lateral offset of the vehicle from the centerline between the consecutive plant rows based upon an identity of the consecutive plant rows in the 3D point cloud; and output steering control signals based upon the determined yaw and lateral offset of the vehicle.

Abstract: An object detection system may apply an object detection model to the first image frame to predict a location of a first bounding box of an object in the first image frame and apply a confidence value to the predicted location of first bounding box. In response to the confidence level exceeding a predetermined threshold, a location of a second bounding box in the second image frame may be estimated based on the location of the first bounding box and non-zero movement of the vehicle. The object detection model is updated based on the estimated location of the second bounding box in the second image frame. A location of a third bounding box in the third image frame is predicted using the updated object detection model. An operation of the vehicle is controlled based on the predicted location of the third bounding box.

Abstract: A first monocular image and a second monocular image are captured from a vehicle. The first monocular image is from a first vantage point and contains a subject at a location. The second monocular is from a second vantage point, different than the first vantage point, and contains the subject at the location. A first initial estimate of coordinates of the location is determined based upon the first monocular image. A second initial estimate of coordinates of the location is determined based upon the second monocular image. A final estimate of coordinates of the location is determined based upon the first initial estimate, the second initial estimate and a distance between the first vantage point and the second vantage point.

Abstract: An image frame streaming system may include a vehicle, a video camera carried by the vehicle to output image frames, a multi-media framework carried by the vehicle and configured to generate a first stream and a second stream from the image frames, a first consumer to receive the first stream and a second consumer to receive the second stream. The first consumer and the second consumer are each selected from a group of consumers consisting of: a neural network; a live video stream presenter; and a historical time clip storage.

Abstract: A vehicle row follow system may include a vehicle comprising at least one sensor to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image of a region forward the vehicle. The system may further include a non-transitory computer readable medium containing instructions to direct a processor to: determine plan row lines in a 2D image; determine a yaw of the vehicle based upon a slope of a heading line relative to a centerline between the plant row lines in the 2D image; determine a lateral offset of the vehicle from the centerline between the consecutive plant rows based upon an identity of the consecutive plant rows in the 3D point cloud; and output steering control signals based upon the determined yaw and lateral offset of the vehicle.

Abstract: An obstruction avoidance system may include a agronomy vehicle, at least one sensor configured to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image, and instructions to direct a processor to capture a particular 2D image and to obtain signals serving as a basis for a particular 3D point cloud; identify an obstruction candidate in the particular 2d image; correlate the obstruction candidate to a portion of the particular 3D point cloud to determine a value for a parameter of the obstruction candidate; classify the obstruction candidate as an obstruction based upon the parameter; and output control signals to alter a state of the agronomy vehicle in response to the obstruction candidate being classified as an obstruction.

Abstract: A plant locating system may include a vehicle supporting a Global Positioning System (GPS) antenna and a monocular camera. The system may further include a plant locating unit comprising a processing unit and a non-transitory computer-readable medium containing instructions to direct the processing unit to: acquire a sample image of a plant of interest captured at a time with the monocular camera at an unknown distance from the plant of interest (POI); determine a geographic location estimate of the GPS antenna at the time; identify a selected portion of the sample image comprising the POI; determine a distance between the POI and the monocular camera based upon the selected portion; and determine a geographic location estimate of the POI based on the geographic location estimate of the GPS antenna at the time and the determined distance between the monocular camera and the POI.

Abstract: A vehicle row follow system may include a vehicle comprising at least one sensor to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image of a region forward the vehicle. The system may further include a non-transitory computer readable medium containing instructions to direct a processor to: determine plan row lines in a 2D image; determine a yaw of the vehicle based upon a slope of a heading line relative to a centerline between the plant row lines in the 2D image; determine a lateral offset of the vehicle from the centerline between the consecutive plant rows based upon an identity of the consecutive plant rows in the 3D point cloud; and output steering control signals based upon the determined yaw and lateral offset of the vehicle.