Focus of this Kansas Corn Commission grant is to develop an automated scouting tool that will aid producers and consultants in detecting pests in corn fields using a camera fixed to a remote controlled ground drone. Specifically, our objectives are to conduct a feasibility study of differing wavelengths of auxiliary light to facilitate computational identification of different corn pests based on wavelength absorption; create computational algorithms to process image files, identify presence of arthropods, and output pest classification and plant loading which will lay the groundwork for a future, under-the-canopy autonomous precision pest management tool that would be capable of creating a field-level map of pest populations.