Stereo Vision Based Position And Posture Estimation Of Parallel Manipulator

Pose is an important parameter reflecting the movement state of a parallel manipulator. However, the problem of measuring the full 6-DOF pose of a parallel manipulator with high accuracy is still urgent to be solved in the movement control of parallel manipulator due to the following three reasons:Firstly, the parallel manipulator usually has complex structure; Secondly, its movement is multi-degree-of-freedom comprehensive one in the three-dimensional space; Thirdly, when there is no any detection device, the precise space position of a parallel manipulator is an unknown quantity which does not obey any laws.To resolve these problems, a pose detection system based on the stereoscopic vision technology has been designed in the thesis for a moving parallel manipulator. Then the algorithms for feature extraction and tracking the moving parallel manipulator are established. Afterward, the pose estimation methods based on monocular vision and binocular vision are proposed to get high accurate movement pose parameters of the parallel manipulator.Firstly, the thesis illustrates the history, the current research and main application fields of the parallel manipulator systematically, analyzes the pose estimation methods and the problems to be solved in the parallel manipulator field, and describes the structure and theory of the machine vision system and the current situation of research and application of machine vision measurement technology.Then, we design a system structure diagram based on the integrated information processing mechanism. For the pose detection of a parallel manipulator, a vision information feedback framework and pose description methods are offered.Next, we extract the parallel manipulator's different types of Haar-like features and set up a completed feature set. Then, we use this completed feature set to train simple classifiers, and sets up a cascaded classifier by different kinds of single and separate classifiers to track the parallel manipulator.Then, we discusses three methods of the parallel manipulator's pose estimation based on the monocular vision:Vision-based pose identification of the parallel manipulator using two affine invariants of a parallelogram; Iterative pose estimation for parallel manipulator using points correspondences; Immune evolutionary algorithm to determine the position and rotation of parallel manipulator. In the first method, two affine invariants of a parallelogram on the parallel manipulator's end-effector are utilized to determine the pose of the moving target relative to the camera. The second method is an iterative one. In the iterative process, results in the first method are used as initial values and the height of the vector from the camera's focus point to the parallel manipulator's end-effector is taken as the variable. Then, a model about this variable and the projection depths of each feature point is established, and an error matrix is also established through seven error functions which are produced by the depth estimation and the co-planarity of the four feature points. Finally, the Gaussian iteration is introduced to estimate the value of the variable, and to obtain the parallel mechanism motion pose information. In the third menthod, six pose parameters (three rotation parameters and three translation parameters) to be estimated are taken as antigens. Then several immune mechanisms (such as the clone and mutation mechanism, the immune remember mechanism) are borrowed to design an immune evolutionary algorithm. Through this evolution process, the best solution vector of six pose parameters can be obtained.Moreover, a pose measurement system based on binocular is built, and a method of calculating the parallel manipulator's pose based on Active Appearance Model (AAM) is proposed. First, two independent AAM models are established:One for the right camera and the other for the left camera. Through an off-line training phase, the parameters of these two AAM models are obtained. Then the end-effector of parallel manipulator is tracked using the trained AAM models. At last, according to the geometry transform relations in projections space and the matched stereo image pairs, the 3D reconstruction and pose estimation of the parallel manipulator is realized.Finally, the work in this thesis is summarized, and several research directions which need to be explored further are listed.