Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot

Abstract

The authors wish to thank Pedro Hernáiz and his team (ICA-CSIC) for their invaluable help in the field trials. The authors wish to acknowledge the invaluable technical support of Damian Rodriguez. Author Contributions: The work was developed as a collaboration among all authors. J.M. Bengochea-Guevara and A Ribeiro designed the study. J.M. Bengochea-Guevara carried out the system integration and programming. D. Andújar posed the field experiments. J. Conesa-Muñoz mainly contributed to the development of the planner and provided support in the field tests with D. Andújar. A. Ribeiro directed the research, collaborating in the testing and the discussion of the results. The manuscript was mainly drafted by J.M. Bengochea-Guevara and A. Ribeiro and was revised and corrected by all co-authors. All authors have read and approved the final manuscript. ; The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them. ; The Spanish Government has provided full and continuing support for this research work through projects AGL2011-30442-C02–02 and AGL2014-52465-C4-3-R. ; We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI). ; Peer reviewed