Abstract: Performance information indicative of operator performance of a mobile machine is received. A performance opportunity space is identified, indicative of possible performance improvement. Savings identified in the performance opportunity space are quantified.

Abstract: Performance information indicative of operator performance of a mobile machine is received. A performance opportunity space is identified, indicative of possible performance improvement. Savings identified in the performance opportunity space are quantified.

Abstract: A steering control method including the steps of obtaining a heading error, obtaining a velocity value, obtaining a distance error, applying the heading error and defuzzifying an output from a steering rule base. The velocity value and the distance error are applied along with the heading error to fuzzy logic membership functions to produce an output that is applied to a steering rule base. An output from the steering rule base is defuzzified to produce a steering signal.

Abstract: The present invention is a method for providing guidance towards a far-point position for a vehicle implementing a satellite-based guidance system. The method 200 includes capturing an image 202. The method 200 further includes providing the image in a digital format to an algorithm 204. The method 200 further includes isolating far-point pixelized data of the provided image 206. The method 200 further includes generating data for causing a steering control system of the vehicle implementing the satellite-based guidance system to maintain the vehicle on a straight-line path towards the far-point position 208.

Abstract: The present invention is a method for providing guidance towards a far-point position for a vehicle implementing a satellite-based guidance system. The method includes capturing an image. The method further includes providing the image in a digital format to an algorithm. The method further includes isolating far-point pixelized data of the provided image. The method further includes generating data for causing a steering control system of the vehicle implementing the satellite-based guidance system to maintain the vehicle on a straight-line path towards the far-point position.

Abstract: The present invention is a method for providing guidance towards a far-point position for a vehicle implementing a satellite-based guidance system. The method includes capturing an image. The method further includes providing the image in a digital format to an algorithm. The method further includes isolating far-point pixelized data of the provided image. The method further includes generating data for causing a steering control system of the vehicle implementing the satellite-based guidance system to maintain the vehicle on a straight-line path towards the far-point position.

Abstract: Machine operators rely on intuition and experience to evaluate vehicle performance. As we increasingly turn to automation, it is important to automatically evaluate sensor data and system performance. Fuzzy logic allows us to take advantage of domain knowledge to evaluate data and to describe a system linguistically. In this application a fuzzy quality module evaluates output from a noisy sensor. It compares the sensor data with an estimated sensor value, and based on that comparison, dynamically adapts a fuzzy logic rulebase used to determine whether the sensor value is valid or not.

Abstract: A combine having a camera system is disclosed in which pictures of the ground in front of the vehicle are processed to extract the slope and intercept of a characteristic line indicative of the boundary between the cut and uncut portions of the field. A fuzzy logic algorithm compares the slope and intercept using four input membership functions and a single output membership function. If the slope and intercept extracted from the image are deemed acceptable, they are used to navigate the vehicle through the field. If they are not acceptable, the combine continues to use slope and intercept values previously deemed acceptable to guide the vehicle. This process of image data extraction and quality analysis continues repetitively as the combine traverses the field harvesting crops.

Abstract: A method and apparatus for detecting an edge between a cut crop and an uncut crop in a field is disclosed. At least two scanlines of pixel data are processed based on an image of the field. A characteristic line corresponding to the cut/uncut edge is best fit between center location points of segments from each scanline using sequential regression analysis. A fuzzy logic algorithm is used to determine whether to continue processing each successive scanline of data based on the quality of the characteristic line. If certain fuzzy membership functions determine that the slope and intercept values have sufficiently converged, processing of the scanlines is completed and the agricultural vehicle is automatically guided along the cut/uncut edge corresponding to the characteristic line.

Abstract: A combine having a camera system is disclosed in which pictures of the ground in front of the vehicle are processed to extract the slope and intercept of a characteristic line indicative of the boundary between the cut and uncut portions of the field. A fuzzy logic algorithm compares the slope and intercept using four input membership functions and a single output membership function. If the slope and intercept extracted from the image are deemed acceptable, they are used to navigate the vehicle through the field. If they are not acceptable, the combine continues to use slope and intercept values previously deemed acceptable to guide the vehicle. This process of image data extraction and quality analysis continues repetitively as the combine traverses the field harvesting crops.

Abstract: A fuzzy steering controller for wheel-type agricultural vehicles with an electrohydraulic steering system is disclosed. The fuzzy controller was developed based on a common-sense model of agricultural vehicle steering. The controller implements steering corrections based upon the desired steering rate and the error between the desired and the actual wheel angles. The controller consists of a variable fuzzifier, an inference engine with a steering control rulebase, and a control signal defuzzifier. The controller could be used on different platforms. Tuning of the fuzzy membership functions will accommodate for physical differences between the platforms. The controller achieves prompt and accurate steering control performance on both a hardware-in-the-loop electrohydraulic steering simulator and on an agricultural tractor.

Abstract: An automatically guided agricultural vehicle with multiple sensors is disclosed. The automatically guided agricultural vehicle includes guidance parameter identification using multi-sensor data fusion for real-time vehicle guidance. To insure robust navigation, a map-based guidance and sensor-based guidance are disclosed and integrated because no individual sensing technology is ideally suited for vehicle automation under all modes of use. The appropriate sensor and operational mode will depend on the field status of time or operation. A fiber optic gyroscope (FOG) and a real-time kinematic GPS (RTK-GPS) and machine vision are added to the guidance system in order to improve reliability of the system for vehicle guidance. The navigator includes key functions of selecting control mode, correcting position by vehicle roll/pitch inclinations, Kalman filtering, and calculating a steering angle.

Abstract: A fuzzy steering controller for wheel-type agricultural vehicles with an electrohydraulic steering system is disclosed. The fuzzy controller was developed based on a common-sense model of agricultural vehicle steering. The controller implements steering corrections based upon the desired steering rate and the error between the desired and the actual wheel angles. The controller consists of a variable fuzzifier, an inference engine with a steering control rulebase, and a control signal defuzzifier. The controller could be used on different platforms. Tuning of the fuzzy membership functions will accommodate for physical differences between the platforms. The controller achieves prompt and accurate steering control performance on both a hardware-in-the-loop electrohydraulic steering simulator and on an agricultural tractor.

Abstract: A combine having a camera system is disclosed in which pictures of the ground in front of the vehicle are processed to extract the slope and intercept of a characteristic line indicative of the boundary between the cut and uncut portions of the field. A fuzzy logic algorithm compares the slope and intercept using four input membership functions and a single output membership function. If the slope and intercept extracted from the image are deemed acceptable, they are used to navigate the vehicle through the field. If they are not acceptable, the combine continues to use slope and intercept values previously deemed acceptable to guide the vehicle. This process of image data extraction and quality analysis continues repetitively as the combine traverses the field harvesting crops.

Abstract: Machine operators rely on intuition and experience to evaluate vehicle performance. As we increasingly turn to automation, it is important to automatically evaluate sensor data and system performance. Fuzzy logic allows us to take advantage of domain knowledge to evaluate data and to describe a system linguistically. In this application a fuzzy quality module evaluates output from a noisy sensor. It compares the sensor data with an estimated sensor value, and based on that comparison, dynamically adapts a fuzzy logic rulebase used to determine whether the sensor value is valid or not.

Abstract: An automatic vision guidance system for an agricultural vehicle is disclosed and described. The vision guidance system uses a K-means clustering algorithm in image processing to distinguish between crop and non-crop features. The vision guidance system utilizes moment algorithms to determine the location and orientation of crop rows, from which desired wheel angles are determined and steering is commanded. The vision guidance system may adjust the location and orientation of visually determined crop rows according to a predetermined distance between crop rows. Further, the vision guidance system may utilize a redundant number of regions of interest in determining crop row locations and orientations.

Abstract: An apparatus and method is disclosed for producing a plurality of video signals to be processed by an image processor, where the video signals are representative of light reflected from a source region, such as a segment of an agricultural field. The apparatus includes a light receiving unit for receiving the light reflected from the source region and a multi-spectral sensor coupled to the light receiving unit for converting the light received by the light receiving unit into the video signals. The multi-spectral sensor includes a prism for dividing the light received by the light receiving unit into a plurality of light components, a plurality of light-detecting arrays each having a plurality of pixels for receiving the light components and producing electronic signals in response thereto, and a sensor control circuit for converting the electronic signals into video signals and for controlling the responsiveness of the pixels of the light detecting arrays to the light components.

Abstract: A multi-spectral imaging system and method for producing an image is disclosed. More specifically, the imaging system produces an image of vegetation for analysis of crop characteristics, such as nitrogen levels, from an area having vegetation and a non-vegetation background. A light sensing unit detects light reflected at multiple wavelengths. The image is segmented into images at different wavelengths such as at the red, green and near infrared wavelengths. The images are combined into a multi-spectral image and segmented into a vegetation image by eliminating all non-vegetation images by using the images at two wavelengths. The vegetation image is analyzed for nitrogen levels by calculating reflectance values at the green wavelength. The images may be stored for further analysis of crop characteristics.

Abstract: A system for automatically detecting the presence of contaminants in samples. The system includes a microscope, controllable stage positioner for holding slides under the microscope, a computer for controlling the stage positioner and a digital camera to capture images through the microscope. The system scans microscope views of regions of a slide sample and provides the digital images to the computer. Image processing routines stored in the computer analyze the digital images and determine whether these images may contain certain contaminants by comparing the characteristics of the objects in the image with the known characteristics of the contaminants.