基于3D目标跟踪算法的机器人手眼协调研究

为了适应环境的复杂性和多样性，增强机器人抓取任务的鲁棒性，本文从3D目标跟踪算法出发，提出了一种实现机器人手眼协调的新方法。该方法采用改进的基于区域的位姿追踪算法同时跟踪机械臂夹持器和目标物体的位姿，根据二者的相对位置关系引导机械臂运动。对基于区域的位姿跟踪算法，本文提出根据局部区域分割线构建分割模型并改进模型颜色似然的线性更新方式，使得算法能够准确跟踪机械臂夹持器与目标物体。基于ROS平台搭建了一套仿真实验环境，并分别在仿真环境和真实环境下验证了此手眼协调系统的有效性和鲁棒性。这种方式不仅不需要手眼标定，更接近于人类“Sensor-Actor”带反馈的闭环控制方式，同时赋予了机器人足够的灵活性来应对弹性的任务和多变的环境。

Hand-eye coordination of robots based on the 3D object tracking algorithm

To adapt to the complexity and diversity of an environment and enhance the robustness of the robot grasping tasks, this paper suggests a novel method to realize the hand-eye coordination of a robot based on the 3D object tracking algorithm. In this method, an improved region-based pose tracking algorithm is used to track the poses of the manipulator and the target and simultaneously guide the manipulator movement according to its relative position. For the region-based pose tracking algorithm, a segmentation model is constructed as per the segmentation lines of the local region, and the linear updating method of the model color likelihoods is improved, to accurately track the gripper and the target. Simulation experiments are conducted based on the ROS platform, and the effectiveness and robustness of the hand-eye coordination system are verified in both the simulation and real environments. This method does not need hand-eye calibration and is closer to the human closed-loop control of the “Sensor-Actor” mode with feedback. Concurrently, it provides robots with enough flexibility to deal with versatile tasks in a modifiable environment.