Research On Machine Vision Measure Techniques And Their Applications In Service Robot Intelligent Space

With the development of technology and the intensified human society aging trend, the demands of using service robot in home environment to accomplish the domestic services such as chatting, accompanying, tea or water delivery have become increasingly urgent. The intelligent space technique, who uses knowledge distribution and intelligent distribution as the main thoughts, and uses the distribution of camera, microphone, temperature sensor, humidity sensor and gas sensor through wireless network technology into the environment as the main means, provides strong support for a service robot to fully perceive the environment, correctly understand people's intent and more effectively provide active service. The combination of intelligent space technology and service robot technology extends the robot's perception and decision-making ability. At the same time, as a removable perception and implementation equipment, the service robot enhances the functionality of intelligent space for information perception and service tasks execution.Human access to80%of the external environment information through eyes, similar to this characteristics, the intelligent space uses camera as the core sensor to perceive the environment information, and uses machine vision measure technique to finish most of the service tasks such as recognition and understanding of human behavior, localization and navigation of service robot, handling and delivering of medicines or cups and so on. The machine vision measure technique is a kind of image processing technique which is used to restore the cameras' Euclidean motion information (position and orientation) and the3D scene structure information through different image views. This dissertation focuses on the machine vision measure technique and its applications in home environment intelligent space, the main contents and results are summarized as follows:(1)The computation and decomposition of two different kinds of homography, which are called homography from a world plane and homography induced by a scene plane, are discussed. The decomposition of the two kinds of hompgraphy is an effective way to acquire the camera relative pose and scene structure from2D image information. Firstly, based on the properties of schur complement, two different types of sparse LM iterative optimization methods are given, and computations of the two kinds of homography are given using the DLT method and LM iterative method respectively. Moreover, for the homography from a world plane, the camera intrinsic parameters, camera relative pose and scene structure are restored using single view or at least three different views in case of camera intrinsic parameters partly known or completely unknown respectively, for the homography induced by a scene plane, a singular value decomposition algorithm is proposed to acquire two solutions verifying a physical constraint, meanwhile a homography decomposition algorithm is given in case of knowing the scene structure, using which we can acquire the unique solution. Finally, the conversion relationship between homogeneous image coordinates based image moments and homogeneous projective coordinates based image moments is derived and the fact that the normalized central moments of the image are absolutely symmetrical inverter tensor is proved under the2D affine transformation, which is applied to educe a new method to compute the corresponding2D affine transformation.(2) The problem of using distributed camera system to locate the moving targets in service robot intelligent space is discussed. Firstly, the robot set to do several known movements, and extract the image correspondence. By using the decomposition of homography from a world plane, the internal and external parameters of the distributed camera system is calibrated. Then using the calibration results, a simple but fast monocular camera based moving target localization algorithm is designed, but the shortages of this algorithm reduces the accuracy when moving target is away from the camera. Finally a binocular camera based moving target localization algorithm is introduced, for the shortcomings of solved moving target's position not on the ground using simple linear triangular method, a constrained linear triangular method is further given, Using the constrained linear triangular method and the LM method refined image points, the binocular camera based moving target localization is accomplished.(3) The problem of using ceiling projection navigation system to realize the visual track navigation method is researched. Firstly the kinematic model of the ceiling laser projector is established, using the model the nonlinear mapping relationship between projector's angular displacement, angular velocity and laser spot's linear displacement, the linear velocity on the ground can be acquired. At the same time in order to transform the planned route from the world coordinate frame to the projector's base coordinate frame, an original projector's external parameter calibration method is proposed. Secondly the mobile service robot is considered to be a3-DOF manipulator, its kinematic model is established, the internal and external parameters of the camera mounted on the robot are calibrated using decomposition of hompgraphy from a world plane, meanwhile consider camera frame as the reference coordinate frame, the3D parameter of ground plane is computed. Finally the adaptive Compensation Tracking Control Law and the Nonlinear State Error Feedback Tracking Control Law are designed respectively to control the service robot so that it can finish the visual servo tracking of the moving laser spot projected on the ground.(4) The problem of localization and recognition of the QR Code based artificial landmark is discussed, which is an important carrier for knowledge distribution and intelligence distribution. Firstly The QR Code based artificial landmark is divided into two categories:the QR Code based artificial object mark used for Global Semantic Map Building and the QR Code based artificial signpost used for Local Navigation Map Building, then the external pattern and internal information encoding are designed respectively. Moreover, by using the blue rectangle area and red circular ring area respectively, two different kinds of QR Code based artificial landmark location mthods are given. Finally, a task function is constructed according to the solved localization information and a position based visual servo control law, which is designed to control the service robot to realize the recognition of the QR Code based artificial landmark.(5) The problem of searching, handling and delivering of the objects dispersed in intelligent space for service robot with one manipulator is researched. Firstly, the QR Code based artificial object mark is designed, which is used to assist the service robot to finish the handling task, and the internal information is coded so that by converting the identification of household objects to the identification of corresponding QR Code, the object mark can reduce the difficulty of the operation for service robot effectively. Moreover by considering the mobile service robot equipped with a manipulator as a generalized manipulator, the kinematic model of the generalized manipulator is established, and certain analytical and numerical methods are given to solve the inverse kinematics, and an original manipulator's hand-eye relationship calibration method is proposed as well. Finally take the mobile robot's non-holonomic constraint into account, a switch object handling control law, which is composed of approximating control law and position based look then doing visual servoing control law, is designed. Under the approximating control law's effect, the service robot approximates the object to be operated under the constraints of gazing, then using the decomposition of homography induced by a scene plane and the known camera motion, the position and pose information between current camera frame and desired camera frame can be computed, and the control law switches to the position based look then doing visual servoing control mode so that the handling operation can finally be accomplished.