Earticle

초록

영어

The measurement value of the traditional binocular parallax distance is the distance between the reference point P and the center of the baseline of the binocular camera, and for the agriculture robot, because of the needs of ground operations, the cameras are usually installed in certain height from the ground with a certain angle with the horizontal direction, when we have to know the horizontal distance from the navigation reference point to the robot body and thus the next travel pose of the robot can be controlled by real-time. Obviously, the traditional binocular parallax distance measuring methods will no longer apply to this. In this regard, a new method for solving agricultural robot navigation reference point distance measurement is proposed. First, conduct calibration for the binocular system with the improved BP neural network, and secondly, obtain the left and right image coordinates of the navigation reference point (U1,V1) (U2,V2) with the improved SIFT features and input the BP neural networks trained in the calibration, and finally, output the coordinates of the navigation reference point in the world coordinate system (X，Y), and then the horizontal distance between the navigation reference point and the robot body can be expressed as S = X2 + Y2 . Experiments show that by this method, the maximum deviation of the actual field experiment test is 0.479cm, with the minimum deviation of 0.032cm, accuracy up to 99%, consuming a total of 55ms. And compared to the traditional binocular parallax distance ranging procedure, the computation is significantly reduced, with certain engineering practicability and feasibility.

목차

Abstract
 1. Introduction
 2. Establishment and Calibration of Agricultural Robot Binocular System
  2.1. Establishment of Binocular System
  2.2. BP Neural Network Calibration
  2.3. Calibration Experiment
 3. Obtaining and Ranging of Field Navigation Reference Point
 4. Experiment and Results Analysis
 5. Conclusion
 Reference

키워드

저자

• Zhang Miao [ College of Science and Information, Qingdao Agricultural University, Qingdao ,Shandong,266109, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605