Research On Robot Target Location Based On Binocular Vision

As an important carrier of intelligent technology,robots have attracted the attention of researchers in related fields.Among them,robot vision realizes the simulation of human eyes,and then perceives and judges the environment,and has broad application prospects.This article is for robot applications,researching the binocular positioning technology of target objects,mainly working on the following aspects:First,calibrate the camera parameters.This paper proposes a circular mark point extraction algorithm based on Blob analysis.It uses a planar circular array calibration plate,which is combined with Zhang Zhengyou's calibration method to complete the camera calibration,with high accuracy.Second,identify specific targets in complex environments.Improve the image quality by filtering and enhancing contrast;propose an edge-cutting algorithm combining Mean-Shift and differential operator,which has good environmental adaptability;study the target recognition of SIFT feature descriptor,and optimize the error by RANSAC algorithm Matching problems,combined with M-LDB descriptors,improve real-time performance.Then,complete 3D reconstruction and target pose estimation.Introduce epipolar geometry to achieve dual target fixation and stereo proofreading;based on homography transformation and epipolar constraint,realize fast and accurate target 3D position estimation;fit target 3D plane,determine posture,and achieve target space positioning.Several sets of comparative experiments are designed to test the accuracy and real-time performance of the positioning algorithm,and analyze the errors.Finally,the hand-eye calibration of the robot system is studied.In order to solve the problem that the traditional linear method is sensitive to noise,an optimized calibration algorithm based on cuckoo search is proposed to reduce the error.Compared with the classic Tsai two-step calibration method,the simulation experiment is carried out.The experimental results show that the algorithm effectively suppresses the environmental noise and improves the positioning accuracy of the hand-eye system.