论文标题
基于非线性优化的操纵器的视觉运动学校准方法
A Visual Kinematics Calibration Method for Manipulator Based on Nonlinear Optimization
论文作者
论文摘要
传统的机械手术器校准方法需要精确的三维测量仪器来测量末端姿势,这不仅是由于测量仪器的高成本,而且不适用于所有操纵器,这不仅是昂贵的。另一种校准方法使用摄像头,但是相机参数引起的系统错误会影响机器人臂运动学的校准精度。因此,本文提出了一种基于单眼视觉的操纵器运动学模型的几何参数的方法。首先,经典的Denavit-Hartenberg(D-H)建模方法用于建立操纵器的运动学参数。其次,进行非线性优化和参数补偿。校准板的特征点的三维位置与对应于实际运动学模型相对应的每个操纵器姿态和经典的D-H运动模型映射到像素坐标系中,并且将两者的像素均值的欧几里得距离误差和两者的像素均值误差总和用于优化目标功能。实验结果表明,末端姿势的像素偏差与本文提出的优化的D-H运动学模型相对应,并且与像素坐标系中实际运动学模型相对应的末端姿势为0.99像素。与经典D-H运动学模型和实际像素坐标计算的像素坐标之间的7.9偏差像素相比,偏差降低了近7个像素,以减少87%的误差。因此,提出的方法可以有效避免视觉校准中的摄像头参数引起的系统错误,可以提高机器人臂结束的绝对定位精度,并且具有良好的经济性和普遍性。
The traditional kinematic calibration method for manipulators requires precise three-dimensional measuring instruments to measure the end pose, which is not only expensive due to the high cost of the measuring instruments but also not applicable to all manipulators. Another calibration method uses a camera, but the system error caused by the camera's parameters affects the calibration accuracy of the kinematics of the robot arm. Therefore, this paper proposes a method for calibrating the geometric parameters of a kinematic model of a manipulator based on monocular vision. Firstly, the classic Denavit-Hartenberg(D-H) modeling method is used to establish the kinematic parameters of the manipulator. Secondly, nonlinear optimization and parameter compensation are performed. The three-dimensional positions of the feature points of the calibration plate under each manipulator attitude corresponding to the actual kinematic model and the classic D-H kinematic model are mapped into the pixel coordinate system, and the sum of Euclidean distance errors of the pixel coordinates of the two is used as the objective function to be optimized. The experimental results show that the pixel deviation of the end pose corresponding to the optimized D-H kinematic model proposed in this paper and the end pose corresponding to the actual kinematic model in the pixel coordinate system is 0.99 pixels. Compared with the 7.9 deviation pixels between the pixel coordinates calculated by the classic D-H kinematic model and the actual pixel coordinates, the deviation is reduced by nearly 7 pixels for an 87% reduction in error. Therefore, the proposed method can effectively avoid system errors caused by camera parameters in visual calibration, can improve the absolute positioning accuracy of the end of the robotic arm, and has good economy and universality.