Liu Chenlu, Ye Chao, Shi Hongzhe, Lin Weiyang
Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel). 2024 Jul 17;24(14):4626. doi: 10.3390/s24144626.
In this paper, a practical discrete-time control method with adaptive image feature prediction for the image-based visual servoing (IBVS) scheme is presented. In the discrete-time IBVS inner-loop/outer-loop control architecture, the time delay caused by image capture and computation is noticed. Considering the dynamic characteristics of a 6-DOF manipulator velocity input system, we propose a linear dynamic model to describe the motion of a robot end effector. Furthermore, for better estimation of image features and smoothing of the robot's velocity input, we propose an adaptive image feature prediction method that employs past image feature data and real robot velocity data to adopt the prediction parameters. The experimental results on a 6-DOF robotic arm demonstrate that the proposed method can ensure system stability and accelerate system convergence.
本文提出了一种用于基于图像的视觉伺服(IBVS)方案的具有自适应图像特征预测的实用离散时间控制方法。在离散时间IBVS内环/外环控制架构中,注意到了图像采集和计算所引起的时间延迟。考虑到六自由度机械手速度输入系统的动态特性,我们提出了一个线性动态模型来描述机器人末端执行器的运动。此外,为了更好地估计图像特征并平滑机器人的速度输入,我们提出了一种自适应图像特征预测方法,该方法利用过去的图像特征数据和实际机器人速度数据来调整预测参数。在六自由度机器人手臂上的实验结果表明,所提出的方法能够确保系统稳定性并加速系统收敛。