本文選題：雙目視覺 + 視覺伺服　； 參考：《湖北工業(yè)大學》2017年碩士論文

【摘要】：基于雙目視覺的串聯(lián)機器人視覺伺服系統(tǒng)能夠直接獲取目標的位置信息和更多的圖像特征,實現(xiàn)了基于視覺的閉環(huán)控制,是視覺伺服的典型結(jié)構(gòu)。本文圍繞著實時性、穩(wěn)定性、準確性將課題分為目標在圖像中的定位、目標在三維中的定位、視覺伺服控制方法、目標位置預測和跟蹤四個部分分析,分別研究其涉及的基本理論和方法,并通過仿真或理論評估這些方法對課題的適用性,探究串聯(lián)機器人實時雙目視覺伺服穩(wěn)定有效的實現(xiàn)方法。(1)使用目標在圖像上的點特征定位目標,并通過對常用點特征提取算法原理和特點的對比,了解到Ransac優(yōu)化Orb算法具有強實時性和穩(wěn)定性。(2)分析了雙目下的目標由圖像空間到三維空間的映射過程,發(fā)現(xiàn)視差的準確性影響著三維定位的準確性。引出了比傳統(tǒng)立體匹配算法更優(yōu)的ELAS立體匹配算法,并針對該算法誤匹配率較高的問題,提出了基于視差連續(xù)性約束的改進ELAS立體匹配算法,至少降低了原算法15.63%的誤匹配率。(3)基于eye-in-hand配置的6自由度串聯(lián)機器人和靜止的點目標,對比了PBVS、IBVS、HBVS的視覺伺服方法。針對現(xiàn)有IBVS中偽逆構(gòu)造法的缺點,提出了基于混合的雅可比偽逆構(gòu)造法,仿真驗證了新構(gòu)造法的有效性。(4)針對運動目標軌跡預測的問題,討論了已知目標運動狀態(tài)下的線性kalman濾波、已知目標運動狀態(tài)下多傳感融合的擴展kalman濾波以及未知目標運動狀態(tài)下的交互多模型的kalman濾波對目標的跟蹤預測,并仿真驗證了這些方法在圖像和三維跟蹤過程中的有效性。在實驗中,跟蹤平穩(wěn)誤差均小于5個像素或5mm。最終獲得了串聯(lián)機器人實時雙目視覺伺服穩(wěn)定有效的實現(xiàn)方法,即使用Ransac-Orb提取目標點特征,使用改進的ELAS求取視差,使用基于基于混合的雅可比偽逆構(gòu)造法的IBVS作為視覺伺服控制律,使用對應場景下的kalman濾波對運動目標進行軌跡預測。
[Abstract]:The visual servo system of series robot based on binocular vision can directly obtain the position information of the target and more image features. It realizes the closed-loop control based on vision and is a typical structure of visual servo. This thesis is divided into four parts: target location in image, target positioning in 3D, visual servo control method, target position prediction and tracking, around real-time, stability and accuracy. The basic theories and methods involved are studied, and the applicability of these methods to the subject is evaluated by simulation or theory. This paper probes into the stable and effective realization method of real-time binocular visual servo of serial robot. It uses the point feature of the target to locate the target on the image, and compares the principle and characteristics of the common point feature extraction algorithm. It is found that the Ransac optimized Orb algorithm has strong real-time and stability. (2) the mapping process from image space to 3D space is analyzed. It is found that the accuracy of parallax affects the accuracy of 3D location. The ELAS stereo matching algorithm is better than the traditional stereo matching algorithm. Aiming at the problem of high mismatch rate, an improved ELAS stereo matching algorithm based on parallax continuity constraint is proposed. At least the mismatch rate of the original algorithm is reduced by 15.63%.) based on the eye-in-hand configuration, the 6-DOF series robot and the stationary point target are compared. The visual servo method of the PBVS IBVS / HBVS is compared. In view of the shortcomings of the existing pseudo inverse construction method in IBVS, a mixed Jacobian pseudo inverse construction method is proposed. The simulation results show that the new construction method is effective to predict the trajectory of moving targets. In this paper, the linear kalman filter with known target motion, the extended kalman filter with multi-sensor fusion and the target tracking prediction with interactive multi-model kalman filter under unknown moving state are discussed. Simulation results show that these methods are effective in image and 3D tracking. In the experiment, the tracking stationary error is less than 5 pixels or 5 mm. Finally, a stable and effective realization method of real-time binocular visual servo of serial robot is obtained, that is, the feature of target point is extracted by Ransac-Orb, and parallax is obtained by using improved ELAS. The IBVS based on the mixed Jacobian pseudo-inverse method is used as the visual servo control law, and the kalman filter in the corresponding scene is used to predict the trajectory of the moving target.
【學位授予單位】：湖北工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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本文編號：1944954