Obstacle avoidance for orchard vehicle trinocular vision system based on coupling of geometric constraint and virtual force field method

Abstract

Nowadays the use of visual navigation in orchard is rapidly growing, while current research mainly focuses on orchard row detection or obstacle detection separately. The economic, fast and reliable navigation vision system that completing orchard row following and obstacle avoidance simultaneously and the obstacle avoidance algorithm for vision system without complex multiple navigation systems combining are needed further research. In this paper, a trinocular vision system for orchard vehicle is set up and the obstacle avoidance algorithm based on coupling of geometric constraint and virtual force field is designed for its vision system.First of all, based on analyzing the different vision system characteristics and the detection demand of orchard obstacle avoidance the trinocular vision system for orchard vehicle is set up based on a wide-angle camera and binocular stereo vision system. Then, the image processing algorithm of orchard row and obstacle detection is designed. For orchard row detection, the trunk regions enhancement algorithm is designed based on grayscale morphology filtering the trunk regions prediction algorithm is designed based on optical flow method to improve the trunk regions detection speed and accuracy. For obstacle detection, the background equalization algorithm based on H-channel image characteristics and the interference weaken algorithm with G-channel image characteristics are designed. Based on the row and obstacle detection results the algorithm for obstacle avoidance in orchard based on coupling of geometric constraint and virtual force field is designed. In the obstacle avoidance process, the virtual force field method is used as the mainly control of the vehicle obstacle avoidance process, and the geometric constraint between visual model of trinocular vision system and obstacle position is coupling with it to fulfill the avoidance demand of the obstacle with special shape and other condition that influence the virtual force field calculation.The experimental results show that the trinocular vision system for orchard vehicle built in this paper has strong adaptability to the actual environment which is accurate and stable for orchard row detection and obstacle detection simultaneously. The average deviation is 4.76 cm and 7.05 cm at 0.5 m/s and 1.0 m/s respectively, the average deviation of obstacle distance detection in the Z-axis direction is 3.18 cm, and in the X-axis direction is 0.45 cm. And the obstacle avoidance algorithm designed in this paper is effective in the orchard which can meet the actual production requirements. The research results will lay a foundation for the development of intelligent equipment and unmanned management in orchard.