本文關(guān)鍵詞：基于視覺手勢識別的機械手操控系統(tǒng)的研究　出處：《天津工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 機械手 手勢識別 體感控制 數(shù)據(jù)處理 操控系統(tǒng)

【摘要】：隨著機器人技術(shù)的飛速發(fā)展,機器人已經(jīng)廣泛地應(yīng)用于生產(chǎn)、生活等各個領(lǐng)域中,人與機器人之間的交互活動也就變得越來越頻繁。但是目前機器人的操控方式卻很單調(diào)、繁瑣,人與機器人之間的交互不夠直觀、自然而且效率比較低。因此,研發(fā)基于視覺的自然手勢交互系統(tǒng)不僅具有一定的學(xué)術(shù)研究價值,而且具有相當大的實際應(yīng)用前景。本文在分析了國內(nèi)外手勢識別和機器人控制系統(tǒng)的相關(guān)研究資料及成果的基礎(chǔ)上,選取了 Leap公司出產(chǎn)的Leap Motion傳感器獲取人手信息,并針對單個傳感器使用時因視覺干擾或者不可避免的遮擋而導(dǎo)致手勢識別準確率降低的現(xiàn)象,研究并實現(xiàn)了一種基于多Leap Motion傳感器的機械手手勢操控系統(tǒng)。這一系統(tǒng)采用多個傳感器在多方位對操作者的手勢進行探測追蹤并進行手勢識別,實現(xiàn)了通過自然手勢控制機械手動作的非接觸式交互。該系統(tǒng)主要包括客戶端(手勢檢測模塊)、信息服務(wù)器端(數(shù)據(jù)處理模塊)、機械手控制器及機械手機構(gòu),文中主要對手勢采集模塊以及數(shù)據(jù)處理模塊進行了研究討論。該文首先介紹了該基于手勢識別的機械手工作原理,然后在對Leap Motion傳感器進行了一定的研究分析后,確定了多個傳感器位置布局,實現(xiàn)了一個基于多傳感器的手勢數(shù)據(jù)采集模塊。該系統(tǒng)中數(shù)據(jù)處理模塊的主要作用是對從多個傳感器獲取的手勢數(shù)據(jù)進行數(shù)據(jù)分析處理,為了更加及時地響應(yīng)人手運動狀態(tài)的變化和獲取較穩(wěn)定、準確的人手位置數(shù)據(jù),本文提出了一種改進的基于"當前"統(tǒng)計模型的自適應(yīng)卡爾曼濾波算法進行濾波和軌跡追蹤;對于通過手指指骨向量計算得到的關(guān)節(jié)角度,采用一種改進的基于均值的加權(quán)滑動均值濾波算法進行穩(wěn)定性濾波平滑處理。當進行手勢的姿態(tài)識別時,將手指關(guān)節(jié)角度等手勢特征向量送入支持向量機(SVM)進行手勢分類,并采用交叉編譯和網(wǎng)格搜索的方法對其參數(shù)進行尋優(yōu),手勢識別準確率可達98.5%。數(shù)據(jù)處理模塊會實時地將位置增量、旋轉(zhuǎn)角度增量或者姿態(tài)動作指令發(fā)送給機械手控制器,機械手控制器會通過內(nèi)部運動學(xué)反解算法得到機械手各個關(guān)節(jié)軸運動數(shù)據(jù)從而驅(qū)動各個伺服電機轉(zhuǎn)動。在最后的系統(tǒng)實驗環(huán)節(jié),操作者通過改變自身手部的空間位置和姿態(tài)達到了手勢操控機械手運動的目的,并驗證了該系統(tǒng)的可用性以及數(shù)據(jù)處理算法的有效性。
[Abstract]:With the rapid development of robot technology, the robot has been widely used in production, life and other fields, the interaction between human and robot becomes more and more frequent. However, the robot is very monotonous, tedious, interaction between human and robot is not intuitive, natural and relatively low efficiency. Therefore, research and development of natural gesture interactive system based on vision not only has a certain academic value, but also has considerable practical application prospect. Based on the analysis of relevant research data and achievements at home and abroad for gesture recognition and robot control system on the selected Leap Motion sensor produced by the Leap company staff get information, and for a single sensor when used for shielding the visual interference or inevitably caused the gesture recognition accuracy decreases, and the implementation of a study Mechanical hand gesture control system based on Motion sensor Leap. Multiple sensors on the operator's gesture in multi azimuth detection tracking and gesture recognition using this system, through the implementation of contactless natural interactive gesture control manipulator movement. The system includes client (gesture detection module, server (information) the data processing module), mechanical manipulator controller and mobile phone structure, this paper focuses on the gesture acquisition module and data processing module are discussed. This paper first introduces the mechanical hand gesture recognition based on the principle of work, and then in the Leap Motion sensor was analyzed after certain to determine the location of layout a sensor, to achieve a gesture based on multi sensor data acquisition module. The main function of data processing module in the system is obtained from multiple sensors The gesture data for data analysis and processing, in order to more timely response to changes in the hand motion state and obtain a stable, accurate hand position data, this paper proposes an improved based on the current statistical model and adaptive Calman filtering algorithm is used for trajectory tracking; joint angle obtained by finger phalanx vector calculation. Using an improved weighted moving average filtering algorithm based on mean stability smoothing. When the attitude recognition of gestures, finger joint angle gesture eigenvector into support vector machine (SVM) method is adopted for gesture classification, cross compiler and grid search to optimize the parameters of gesture recognition the accuracy of 98.5%. data processing module in real time position incremental, rotation angle increment or gestures instructions sent to the manipulator control The controller, the robot controller through the internal inverse kinematics algorithm of manipulator joints motion data obtained thereby each servo motor rotation. In the last part of the experiment system, the operator by changing the spatial position and posture of the hand to motion gesture control manipulator, and validate the availability of the system and data processing algorithms.

【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TP242

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本文編號：1395020