In an embodiment, autonomous vehicles with global positioning systems (GPS) are used for field inspection to reduce fuel and labor costs and improve reliability with increased consistency in
field crop inspection. A vehicle may be programmed to
traverse a field while using sensors to detect objects and operating in a first
image capture mode, for example, capturing low-resolution images of objects in the field, typically crops. Under
program control,
machine vision techniques are used with the low-resolution images to recognize crops, non-
crop plant material or undefined objects. Under
program control,
location data is used to correlate recognized objects with digitally stored field maps to resolve whether a particular object is in a location at which
crop planting is expected or not expected. Under
program control, depending on whether an object in a low-resolution
digital image is recognized as a
crop, and whether the object is in an expected geo-location for crops, the vehicle may cease traversing temporarily and switch to a second
image capture mode, for example, capturing a high-resolution image of the object, for use in
disease analysis or classification,
weed analysis or classification, alert notifications or other messages, or other
processing. In this manner, a field may be rapidly traversed and imaged using coarse-level, rapid techniques that require lower
processing resources, storage or memory, while automatically switching to execute special
processing only when necessary to resolve unexpected objects or to perform operations such as
disease classification that benefit from high-resolution images and more intensive use of processing resources, storage or memory.