Review on Applicability of Vision-based Detection Technology in Field Obstacle Detection

Abstract

In order for robotized field operation by agricultural machineries and complete replacement of manual work in field operation, autonomous obstacle avoidance of agricultural machineries during field operation becomes a critical technology to be solved. For this technology, it is an indispensable requirement and critical premise to timely and accurately perceive static and dynamic information of field obstacles. Firstly, this paper analyzes and determines what obstacles are the target obstacles in the field operation of agricultural machineries from the two aspects - whether the obstacles hinder current operation and whether the obstacles hinder current obstacle avoidance process. Subsequently, this paper mainly discusses the applicability of obstacle detection methods based on monocular vision and binocular stereo vision in field environment: the main existing monocular vision-based methods to detect obstacles are summarized, and their restraints for detecting obstacles in the field are analyzed; considering that precise stereo matching of image pairs is the most complicated and time-consuming part of binocular vision-based detection methods, currently used typical stereo matching algorithms are summarized and compared, and their applicability in field obstacle detection is discussed. At last, the research direction is prospected, and a tendency to detect obstacles for agricultural machineries during field operation is based on multi-sensor fusion system with vision sensor as one of the main sensors.