【作者】 唐新星；

【导师】 赵丁选；

【作者基本信息】 吉林大学 ， 机械电子工程， 2007， 博士

【摘要】 论文结合国家自然科学基金资助项目(编号:50475011),依托于吉林大学机械电子工程实验室的遥操作工程机器人试验平台,建立了“基于立体视觉的遥操作工程机器人自主作业控制系统”,进行了遥操作机器人自主作业时的作业对象自主识别、作业路径规划与抓取检测技术的研究工作。论文所做的主要工作如下:(1)在现场工程机器人上安装了三目摄像机,三目摄像机一方面代替普通摄像机为工程机器人提供视觉反馈,另一方面通过图像采集与处理、识别计算出目标物体的空间坐标;(2)依据识别得到的目标物体的空间坐标,在工程机器人运动学分析的基础上,进行了工程机器人作业路径规划的研究,制定了路径规划所需的算法;(3)研究了自主作业过程中目标物体是否被抓取、夹持及被施放的检测方法,通过试验定量地确定了抓取、夹持不同物体时所施加不同夹持力的大小;(4)在基于立体视觉的遥操作工程机器人试验台上做了自主作业试验。试验结果表明,该自主作业系统已经能够完成对较硬的石块、较软的胶胎等典型作业对象的自主抓取及定点移动作业。更多还原

【Abstract】 During the process of exploitation of the sea, underground resources and astrospace, Tasks are often carried out in the limit working environment which is difficult or hazardous for mankind to approach such as high temperature, high pressure, strong radiation, suffocation etc. In order to complete the complex operations in such harsh circumstances, the teleoperation construction robot technology based on the telepresence has been used widely. Due to the interference of the cosmic rays and the limitation of the transfer condition, the signals being sent back are always with noises and remarkable length of time-delay, the system will be unable to work normally in severe situation. In recent years, the teleoperation construction robot system has autonomous function has been asked for. When the the transmission lines are disrupted and teleoperation can not be carried out, the autonomous task system still can complete the key task which must completed in the part-time independent nodes automatically. Such research and development have great theoretical significance practical value.This dissertation combines the project of national natural science fund (No. 50475011), does extensive investigation on domestic and international research on robot stereo vision technique and robot autonomous path planning, relies on the experiment platform of four degree of freedom teleoperation hydraulic-servo manipulator in mechatronic engineering laboratory of Jilin University, sets up a complete "Autonomous Task Control System of Construction Robot Based on Stereo Vision", and researches and developes the the autonomous task control system of the construction robot. In order to realize the Autonomous Task of construction robot, the dissertation firstly studied the the recongnition of target object and space location technology. the calculation method of the three-dimensional space position is studied by installing Trinocular Stereo carema and collecting two-dimensional images of target object. Which include camera calibration, image preprocessing, stereo matching etc, for eradicate the camera distortion. After gaining the position information in three-dimensional space of the target object, three-dimensional reconstruction of the target object technology is researched. During the process of the camera calibration, neural network technology is applied, compared to traditional camera calibration technology, nonlinear modeling of the cameras is avoided, camera calibration accuracy is enhanced and more accurate depth information of the target object is obtained. In the process of image preprocessing, the image segemation algorithm based on fuzzy threshold is presented, the effective information of target object is extracted successfully, which established the foundation to further image edge correction and the depth information gaining of the target object.Secondly, in order to carry out the autonomous control, the manipulator kinematics modeling, manipulator trajectory planning and control are researched. The construction robot path planning is implementded on the basis of the construction robot inverse kinematics. In order to realize the smooth manipulator movement, the function of the planned trajectory must be continuous and smooth. So for trajectory planning design, Cartesian coordinates are chosen. To meet the requirements of operation precision, the path mid-points interpolation operation were calculated according to the set trajectory path, and returned to the joint space point by point.Thirdly, in order to complete the autonomous task with high quality, capture detection and clamp judgment technology between the manipulator and the target object were studied in this dissertation. Capture detection and clamping judgment are the basis judge that whether the target object has been transfered to appointed position according to the pre-setting path. Finally, in order to test the validity of the proposed control theory and control algorithm, the autonomous task control experiments are carried out on the remote robot platform. The test contents include identification of target objects and spatial positioning, trajectory planning and capture judgment. The main research works have been accomplished as follow:(1) The teleoperation construction robot was taken as the study object, stereo vision is applied into the teleoperation construction robot field for the first time, and the teleoperation construction robot autonomous task experimental system based on stereo vision technology are structured. And by successful trajectory planning and target grasp detection and control, the autonomous task of construction robot is preliminarily realized.(2) In image segmentation, on the basis of traditional fuzzy threshold segmentation, the fuzzy threshold segmentation method based on the trapezoidal fuzzy membership function is presented, which succeeded in achieving an effective information on the target object extraction. And object edge correction, the image matching and calculation of the depth information were proceeded based on the image segmentation.(3) Image matching algorithm based on the edge is presented, the geometric model on the the three eyes camera depth calculation is built for the first time by using space analytic geometry and image superposition, and the 3D reconstruction of the target object is proceeded.Research works show that the autonomous task control system of the construction robot based on the stereo vision technology have preliminarily been able to complete their task, and the task process is smooth. The reasearch work done in this article provided valuable experience and success examples for the deeper autonomous task technology of the teleoperation robot in the future.更多还原