Journal of Terramechanics, Volume 50, Issue 3, June 2013, Pages 211-232, ISSN 0022-4898 http://dx.doi.org/10.1016/j.jterra.2013.03.004. http://www.sciencedirect.com/science/article/pii/S0022489813000220
Abstract: With the predicted increase in world population to over 10 billion, by the year 2050, growth in agricultural output needs to be continued. Considering this, autonomous vehicles application in precision agriculture is one of the main issues to be regarded noteworthy to improve the efficiency. In this research many papers on autonomous farm vehicles are reviewed from navigation systems viewpoint. All navigation systems are categorized in six classes: dead reckoning, image processing, statistical based developed algorithms, fuzzy logic control, neural network and genetic algorithm, and Kalman filter based. Researches in many agricultural operations from water monitoring to aerial crop scouting revealed that the centimeter level accuracy in all techniques is available and the velocity range for evaluated autonomous vehicles almost is smaller than 1 m/s. Finally it would be concluded although many developments in agricultural automation using different techniques and algorithms are obtained especially in recent years, more works are required to acquire farmer’s consensus about autonomous vehicles. Additionally some issues such as safety, economy, implement standardization and technical service support in the entire world are merit to consideration.
Keywords: Autonomous; Navigation; Machine vision; Robot; Kalman filter