服务机器人手眼协调仿生控制研究
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摘要
随着服务机器人的飞速发展及广泛应用，对服务功能的要求也越来越高。近年来，受神经生物学、生物视觉的启发，机器人手眼协调仿生控制技术越来越受到众多学者的青睐，成为近年来机器人研究领域的热点。
本文开展的研究工作受到国家高技术研究发展计划（863计划）项目以及上海市科委重点项目的支持。本文以自主研发的服务机器人为研究对象，深入研究了服务机器人目标识别与定位、静态目标抓取及动态目标跟踪的手眼协调仿生控制等内容，并通过实验进行了验证。论文主要内容如下：
1、介绍了基于立体视觉和轻量化手臂的轮式全向移动服务机器人架构。采用三目立体视觉系统、代码开放的模块化关节型手臂，全向轮式移动机构，以及工业PC控制器，重量小、运动灵活，体现了新一代服务机器人智能化、开放化、可重构化、PC化的发展要求。
2、在服务机器人目标识别方面，研究了基于Contourlet变换域隐马尔可夫树模型的方向多尺度图像边缘特征提取算法，以及改进的归一化互相关特征匹配算法。
近年来国内外学者虽然提出了很多图像边缘特征提取算法，但基本都不具有类似人眼的方向特性，不能最优地表示含面奇异，或者含线奇异的高维函数。而在高维空间中，具有面奇异，以及线奇异的高维函数十分普遍，譬如，物体表面不连续的光滑边界就具有线奇异。为了弥补这种缺陷，本文基于人眼视觉的方向多尺度特性，结合图像方向多尺度几何分析理论，深入研究了基于Contourlet变换域隐马尔可夫树模型的图像边缘特征提取方法。该方法不仅具有小波的时频局域特性和多分辨特性，还具有方向性和各向异性，是高维函数的最优表示方法，是高维复杂视觉图像边缘检测的有效工具。其优势在于提取方向信息、细节信息的能力很强，特别适合于圆形、椭圆形、不规则形状等具有多方向性图案或物体的识别。这是小波分析、Canny算子等方法无法媲美的。在服务机器人目标识别方面具有广泛的应用价值与前景。
在特征匹配方面，由于归一化互相关匹配算法虽然抗噪声能力强、匹配准确，但互相关系数计算量大，要提高匹配速度，必须简化计算。为此，本文引入了卷积运算，把卷积应用于归一化互相关系数计算当中，大大简化了计算，有效提高了系统的实时性。
3、在服务机器人目标位置测量方面，基于人眼双目立体视觉成像机理，利用对极约束原理和双目立体视觉成像系统模型，分析了立体匹配算法，提出了基于对极几何和单应矩阵的立体匹配及误匹配剔除算法，提高了目标位置测量精度。
4、在服务机器人静态目标物体抓取方面，分析了人体手眼协调“最优轨迹”运动机理，给出了人体手眼协调运动数学模型，建立了服务机器人手臂运动学模型，对服务机器人手臂在目标抓取时的路径，进行了仿生运动规划，使得手臂末端执行器沿“最优轨迹”运动，运动轨迹近似直线，速度曲线近似钟形，运动平稳。通过实验验证，服务机器人能够按照仿生运动轨迹抓取目标物体。
5、在服务机器人动态目标跟踪方面，对服务机器人手臂在动态目标跟踪时的路径，进行了仿生运动规划，使得手臂末端执行器沿“最优轨迹”运动，点到点之间的分段运动轨迹近似直线，速度曲线近似钟形，运动平稳，并通过实验进行了验证。
本文利用立体视觉反馈信息，通过手眼仿生控制，研究并实现了三维空间中静态目标抓取，以及动态目标跟踪，这些研究成果将有助于开放式系统下机器人智能化、模块化、PC化、仿生化，以及多传感信息融合等技术的提高，将对拓展机器人的应用领域，具有积极的学术意义和重要的实际意义。
With the rapid development and wide use of service robots, the requierments onservice function become higher and higher. In recent years, inspired by neurobiologyand biological vision, biologically motivated hand-eye coordination controltechniques became a hotspot in the field of robotics research, and many scholars, athome and abroad, did lots of researches on it.
The research carried out in this dissertation was supported by the key projectsfrom the State High-Tech Development Plan (863program) of China, and the keyprojects from Shanghai Science and Technology Commission. All the research workwas done on the service robot made by my Lab..This dissertation is mainly focused onthe research of target object identification and localization, static target grasping andmoving target tracking. They are described in detail as following.
(1) The structure and components of the service robot were introduced in detail inthis dissertation. The service robot is an omni-directional mobile robot, equiped withtrinocular stereo vision and modular arm. The arm is light, flexible, and can becontrolled to grasp static target object, and track moving target object as well, underthe guidence of stereo vision. The service robot is intelligent, open-coded, andreconfigurable. It shows the characteristics of modern service robot.
(2) The image edge feature extraction algorithm based on Contourlet HiddenMarkov Tree Model (HMT in short), and the feature matching algorithm based on theimproved normalized cross-correlation were studied in this dissertation.
In recent years, although lots of image edge feature extraction algorithms wereresearched, most of them couldn’t give a optimal expression for the high-dimensionalfunctions including line, or surface singularity. However, the function with a line orsurface singularity is very common in the high-dimensional space. For example, thediscontinuity of smooth boundary of some object is often shown as a line singular onthe smooth curve. In order to remedy the deficiency, the method on direcectionalmultiscale image edge feature extraction based on Contourlet HMT, was studieddeeply in this dissertation. This method is based on image multiscale geometricanalysis theory and human visual characteristics. This method provides the optimalrepresentation of high dimentional function, and is effective for the edge detection ofhigh dimensional image, because of its characteristics of directionality, anisotropy, multi-resolution, and time-frequency like wavelet. With the superiority in capturingdirectional information, contourlet HMT gives satisfactory recognition performancefor multi-directional components (such as circular and irregular shapes), and will bewidely used in the field of service robot for target object recognition.
About feature matching, although it is accurate and anti-noise to match with thenormalized cross-correlation algorithm, the coefficient is difficult andtime-consuming to be gotten. It is necessary to simplify the calculation of coefficientso as to improve the speed of matching. In order to solve this problem, theconvolution was used to calculate the coefficient. By this way, the calculation speedwas improved highly
(3) In order to get the position of the target object, the algorithm of stereomatching was researched in this dissertation. According to the imaging mechanism ofhuman binocular steero vision, the matching algorithm was proposed based onepipolar geometry and homography constraints. The accuracy of localization wasimproved greatly by the algorithm.
(4) The optimal trajectory of human hand movement was analyzed, and themathematical model of it was given. Based on the mathematical model, kinematicmodel of the robot arm was established, and the bionic path, along which the robotwas controlled to grasp target object, was planned. The robot can be controlled tograsp target object along straight line trajectory, and its speed curve is bell-shaped.According to experiment, the service robot can be controlled to grasp the target objectaccurately and smoothly along the bionic trajectory.
(5) As for the dynamic target object tracking of the service robot, the bionic pathwas planned with the mathematical model of human hand-eye coordination.According to the experiment, the sevice robot can be controlled to move smoothly totrack the target object.
The research work done in this dissertation is very helpful to improve thecapability, and expand the application fields of service robots.
本文开展的研究工作受到国家高技术研究发展计划（863计划）项目以及上海市科委重点项目的支持。本文以自主研发的服务机器人为研究对象，深入研究了服务机器人目标识别与定位、静态目标抓取及动态目标跟踪的手眼协调仿生控制等内容，并通过实验进行了验证。论文主要内容如下：
1、介绍了基于立体视觉和轻量化手臂的轮式全向移动服务机器人架构。采用三目立体视觉系统、代码开放的模块化关节型手臂，全向轮式移动机构，以及工业PC控制器，重量小、运动灵活，体现了新一代服务机器人智能化、开放化、可重构化、PC化的发展要求。
2、在服务机器人目标识别方面，研究了基于Contourlet变换域隐马尔可夫树模型的方向多尺度图像边缘特征提取算法，以及改进的归一化互相关特征匹配算法。
近年来国内外学者虽然提出了很多图像边缘特征提取算法，但基本都不具有类似人眼的方向特性，不能最优地表示含面奇异，或者含线奇异的高维函数。而在高维空间中，具有面奇异，以及线奇异的高维函数十分普遍，譬如，物体表面不连续的光滑边界就具有线奇异。为了弥补这种缺陷，本文基于人眼视觉的方向多尺度特性，结合图像方向多尺度几何分析理论，深入研究了基于Contourlet变换域隐马尔可夫树模型的图像边缘特征提取方法。该方法不仅具有小波的时频局域特性和多分辨特性，还具有方向性和各向异性，是高维函数的最优表示方法，是高维复杂视觉图像边缘检测的有效工具。其优势在于提取方向信息、细节信息的能力很强，特别适合于圆形、椭圆形、不规则形状等具有多方向性图案或物体的识别。这是小波分析、Canny算子等方法无法媲美的。在服务机器人目标识别方面具有广泛的应用价值与前景。
在特征匹配方面，由于归一化互相关匹配算法虽然抗噪声能力强、匹配准确，但互相关系数计算量大，要提高匹配速度，必须简化计算。为此，本文引入了卷积运算，把卷积应用于归一化互相关系数计算当中，大大简化了计算，有效提高了系统的实时性。
3、在服务机器人目标位置测量方面，基于人眼双目立体视觉成像机理，利用对极约束原理和双目立体视觉成像系统模型，分析了立体匹配算法，提出了基于对极几何和单应矩阵的立体匹配及误匹配剔除算法，提高了目标位置测量精度。
4、在服务机器人静态目标物体抓取方面，分析了人体手眼协调“最优轨迹”运动机理，给出了人体手眼协调运动数学模型，建立了服务机器人手臂运动学模型，对服务机器人手臂在目标抓取时的路径，进行了仿生运动规划，使得手臂末端执行器沿“最优轨迹”运动，运动轨迹近似直线，速度曲线近似钟形，运动平稳。通过实验验证，服务机器人能够按照仿生运动轨迹抓取目标物体。
5、在服务机器人动态目标跟踪方面，对服务机器人手臂在动态目标跟踪时的路径，进行了仿生运动规划，使得手臂末端执行器沿“最优轨迹”运动，点到点之间的分段运动轨迹近似直线，速度曲线近似钟形，运动平稳，并通过实验进行了验证。
本文利用立体视觉反馈信息，通过手眼仿生控制，研究并实现了三维空间中静态目标抓取，以及动态目标跟踪，这些研究成果将有助于开放式系统下机器人智能化、模块化、PC化、仿生化，以及多传感信息融合等技术的提高，将对拓展机器人的应用领域，具有积极的学术意义和重要的实际意义。
With the rapid development and wide use of service robots, the requierments onservice function become higher and higher. In recent years, inspired by neurobiologyand biological vision, biologically motivated hand-eye coordination controltechniques became a hotspot in the field of robotics research, and many scholars, athome and abroad, did lots of researches on it.
The research carried out in this dissertation was supported by the key projectsfrom the State High-Tech Development Plan (863program) of China, and the keyprojects from Shanghai Science and Technology Commission. All the research workwas done on the service robot made by my Lab..This dissertation is mainly focused onthe research of target object identification and localization, static target grasping andmoving target tracking. They are described in detail as following.
(1) The structure and components of the service robot were introduced in detail inthis dissertation. The service robot is an omni-directional mobile robot, equiped withtrinocular stereo vision and modular arm. The arm is light, flexible, and can becontrolled to grasp static target object, and track moving target object as well, underthe guidence of stereo vision. The service robot is intelligent, open-coded, andreconfigurable. It shows the characteristics of modern service robot.
(2) The image edge feature extraction algorithm based on Contourlet HiddenMarkov Tree Model (HMT in short), and the feature matching algorithm based on theimproved normalized cross-correlation were studied in this dissertation.
In recent years, although lots of image edge feature extraction algorithms wereresearched, most of them couldn’t give a optimal expression for the high-dimensionalfunctions including line, or surface singularity. However, the function with a line orsurface singularity is very common in the high-dimensional space. For example, thediscontinuity of smooth boundary of some object is often shown as a line singular onthe smooth curve. In order to remedy the deficiency, the method on direcectionalmultiscale image edge feature extraction based on Contourlet HMT, was studieddeeply in this dissertation. This method is based on image multiscale geometricanalysis theory and human visual characteristics. This method provides the optimalrepresentation of high dimentional function, and is effective for the edge detection ofhigh dimensional image, because of its characteristics of directionality, anisotropy, multi-resolution, and time-frequency like wavelet. With the superiority in capturingdirectional information, contourlet HMT gives satisfactory recognition performancefor multi-directional components (such as circular and irregular shapes), and will bewidely used in the field of service robot for target object recognition.
About feature matching, although it is accurate and anti-noise to match with thenormalized cross-correlation algorithm, the coefficient is difficult andtime-consuming to be gotten. It is necessary to simplify the calculation of coefficientso as to improve the speed of matching. In order to solve this problem, theconvolution was used to calculate the coefficient. By this way, the calculation speedwas improved highly
(3) In order to get the position of the target object, the algorithm of stereomatching was researched in this dissertation. According to the imaging mechanism ofhuman binocular steero vision, the matching algorithm was proposed based onepipolar geometry and homography constraints. The accuracy of localization wasimproved greatly by the algorithm.
(4) The optimal trajectory of human hand movement was analyzed, and themathematical model of it was given. Based on the mathematical model, kinematicmodel of the robot arm was established, and the bionic path, along which the robotwas controlled to grasp target object, was planned. The robot can be controlled tograsp target object along straight line trajectory, and its speed curve is bell-shaped.According to experiment, the service robot can be controlled to grasp the target objectaccurately and smoothly along the bionic trajectory.
(5) As for the dynamic target object tracking of the service robot, the bionic pathwas planned with the mathematical model of human hand-eye coordination.According to the experiment, the sevice robot can be controlled to move smoothly totrack the target object.
The research work done in this dissertation is very helpful to improve thecapability, and expand the application fields of service robots.
引文
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