A New Stereo Vision Measurement System For Position And Orientation Of Parallel Robot

In the control of multi-degree of freedom (MDOF) parallel robot, the position and orientation of MDOF parallel robot is a very important motion state parameter. The MDOF parallel robot has complicated motion trails. Compared with tradition measurement methods, computer vision based measurement system has the advantage of intelligence, non-touch and more fast. The position and orientation measurement of MDOF parallel robot with high precision is a unresolved problem. In this thesis, the position and orientation measurement system for 6-DOF parallel robot is built based on machine vision theory. The sampling is actualized by images at different moments and then to intelligently extract the motion information from it. The position and orientation information of 6-DOF parallel robot is further analyzed and computed.This thesis presents a framework of scale-invariant feature transform based stereo vision position and orientation measurement system for a 6-DOF redundant actuation parallel mechanism with 10 inputs. The result of real-time pose can be calculated and displayed by the system. It is composed of image gather and transfer, camera calibration, scale-invariant feature transform (SIFT), reconstruct of points and position and orientation measurement. Main steps are as follows.First, a simple linear calibration method based on pin-hole model is used to calibrate the stereo vision position and orientation measurement system for parallel robot.Second, an acquisition and display simulation system of vision information based on LabView is built. It can observe the object state dynamically.Next, a processing system using SIFT is built. This framework is mainly based on scale-invariant feature transform. It performs reliable matching between different views of objects, when the images have change in scale, rotation, shift and change in illumination. It is especially adapt to measurement for multiple DOF parallel robot and complex motions in space. Finally, the parameter of pose can be calculated by matrixes of translation and rotation of 3D, and then is converted into an optimization problem. The result is optimized by improved particle swarm optimization (PSO) to improve the precision ensuring the high speed of the process. In the end, position and orientation measurement for parallel robot is realized by Matlab program.The results of simulation experiments prove the veracity and validity of all algorithms in this thesis.