Abstract: Techniques for multi-modal contextualization of object detection for use with an agricultural vehicle are described herein. The techniques can provide additional context information to radar detection to assess the likelihood of an object detected by radar of being an object of interest. Examples of detection that might be detected by a radar sensor that, based on the additional context information, the agricultural vehicle can make a determination to ignore can include ground targets, ghost targets, side or overhead reflections from obstacles, detections from tall crops/weeds in a field.

Abstract: Techniques for multi-modal contextualization of object detection for use with an agricultural vehicle are described herein. The techniques can provide additional context information to radar detection to assess the likelihood of an object detected by radar of being an object of interest. Examples of detection that might be detected by a radar sensor that, based on the additional context information, the agricultural vehicle can make a determination to ignore can include ground targets, ghost targets, side or overhead reflections from obstacles, detections from tall crops/weeds in a field.

Abstract: In one aspect, a safety system for a towed implement may include an implement frame structured to be towed by a work vehicle. The safety system may also include an object detection sensor affixed to the implement frame with a field of view sized to capture an image scene in proximity to the implement frame, the object detection sensor structured to generate a scene signal representing the image scene. The safety system may also include a safety control system configured to generate a safety control signal based on a detection data signal, the detection data signal based on a determination of whether an object is detected in the scene signal, the detection data signal having a positive object detection indication if the object is within the image scene of the object detection sensor and a negative object detection indication if the object is not detected within the image scene.

Abstract: In one aspect, a system for detecting worn or damaged components of an agricultural machine may include first and second acoustic sensors positioned at first and second locations on the agricultural machine, respectively, with the second location being spaced apart from the first location. A controller of the system may be configured to determine a first acoustic parameter associated with the first location of the agricultural machine based on acoustic data received from the first acoustic sensor. The controller may also be configured to determine a second acoustic parameter associated with the second location of the agricultural machine based on acoustic data received from the second acoustic sensor. Furthermore, the controller may be configured to determine a component of the agricultural machine is worn or damaged when the first acoustic parameter differs from the second acoustic parameter by a predetermined amount.

Abstract: In one aspect, a system for detecting worn or damaged components of an agricultural machine may include first and second acoustic sensors positioned at first and second locations on the agricultural machine, respectively, with the second location being spaced apart from the first location. A controller of the system may be configured to determine a first acoustic parameter associated with the first location of the agricultural machine based on acoustic data received from the first acoustic sensor. The controller may also be configured to determine a second acoustic parameter associated with the second location of the agricultural machine based on acoustic data received from the second acoustic sensor. Furthermore, the controller may be configured to determine a component of the agricultural machine is worn or damaged when the first acoustic parameter differs from the second acoustic parameter by a predetermined amount.