Control Technique And Kinematic Calibration Of Delta Robot Based On Computer Vision

In close combination with the electron, light industry, food and medicine ofautomation production line for high speed and light load handling requirements, thisdissertation presentsa series of relevant key topics, including robot control based onthe computer vision, fast kinematic calibration, and integrated calibration of visionsystem-robot-production line that can be employed toconfigure a low mobilityhigh-speed parallel robot with vision function.The following contributions have beenmade.A vision-based control system with dynamic position-based look-and-movestructure is designed to perform high frequency pick-and-place tasks on automationproduct line. The major merits can be summarized in brief.(1) Vision system calibration. A camera calibration method based on locallinearization is proposed. By utilizing a square target, only one picture is needed tocalibrate the camera.(2) Target angle recognition. An angle recognition algorithm based on discretearray of object-boundary in polar coordinate is proposed to solve the positioningproblem where the target rotating around the z axis. The algorithm has the advantageof high speed and precision.(3) Target tracking and grasping. A method based on servomotor+synchronous-conveyor is proposed for multiple objects’ tracking and grasping. Byutilizing the encoder of the servomotor, duplication or omission of multiple objects’identifying is avoided. Besides, Newton’s dichotomy method is used for object’sgrasping position calculation. The method fulfills the high frequency pick-and-placeoperation in real time.In the respect of robot kinematic calibration, a fast calibration method using “monocular vision+laser displacement sensor” as is investigated, which can becarried out in fieldwork and improves the robot precision obviously. The major meritscan be summarized in brief.(1) Robot error modeling. An error modeling technique is developed for thekinematic calibration of Delta robot. The model allows the geometric errors affectingthe position and orientation accuracy of the end-effector to be separated into thecompensable and the uncompensable. Error sensitivity analysis is made to reach theconclusion that boundary error is the most sensitive, thus reveals that themeasurement of the error in direction x and y in whole space and the error in directionz at some particular points is enough for the identification of the geometric errorparameter, which provides theoretical basis for error measurement and parameteridentification.(2) Error measurement and parameter identification. By utilizing P4P method,the error of the robot end-effctor in direction x and y is measured in the mode that theCCD camera is moving with the end-effector and the calibration target is fixed underthe workspace. Besides, by utilizing laser displacement sensor, error in direction z ismeasured. Then the parameters can be identified effectively. The positioningaccuracy is upgraded to0.1mm from1mm after the compensation.A monocular vision measurement based method is proposed in the respect of theintegrated calibration of vision system-robot-production line. The rotation about zaxis between vision system and the production line system is calibrated by utilizingthe conveyor’s distance property. Then the calibration of robot with production line isrealized by using P4P method with the help of a simple calibration target. Theproposed method brings adequate guarantee for the overall accuracy of the robotsystem.The outcome has important theoretical meaning and practical value in the visionbased robot technology and engineering application of parallel robot.