Tracking and grasping of moving target based on accelerated geometric particle filter on colored image
Tracking and grasping of moving target based on accelerated geometric particle filter on colored image
复制标题
基于彩色图像加速几何粒子滤波的运动目标跟踪抓取
DOI：
10.1007/s11431-020-1688-2
复制
发表时间：
2020-09-15
影响因子：
4.6
通讯作者：
Ding Han
中科院分区：
文献类型：
--
作者：
Gong ZeYu;Qiu ChunRong;Ding Han
运动物体的视觉跟踪与抓取是机器人操作领域的一个具有挑战性的课题，在人机协作等领域也具有巨大的应用潜力。基于粒子滤波框架和基于位置的视觉伺服，提出了一种随机运动物体的视觉跟踪与抓取新方法。建立了用于视觉跟踪的几何粒子滤波跟踪器。为了解决粒子滤波的跟踪效率问题，采用边缘检测和形态扩张来减少几何粒子滤波的计算量。同时，利用HSV图像特征代替灰度特征，提高了跟踪算法对光照变化的鲁棒性。采用跟踪与拦截相结合的抓取策略，结合基于位置的视觉伺服（PBVS）方法实现对目标的稳定抓取。通过对开源数据集的综合比较和对真实机器人系统的大量实验，证明了该方法在随机运动目标跟踪和抓取方面具有较好的性能。
Visual tracking and grasping of moving object is a challenging task in the field of robotic manipulation, which also has great potential in applications such as human-robot collaboration. Based on the particle filtering framework and position-based visual servoing, this paper proposes a new method for visual tracking and grasping of randomly moving objects. A geometric particle filter tracker is established for visual tracking. In order to deal with the tracking efficiency issue for particle filter, edge detection and morphological dilation are employed to reduce the computation burden of geometric particle filtering. Meanwhile, the HSV image feature is employed instead of the grayscale feature to improve the tracking algorithm’s robustness to illumination change. A grasping strategy combining tracking and interception is adopted along with the position-based visual servoing (PBVS) method to achieve stable grasp of the target. Comprehensive comparisons on open source dataset and a large number of experiments on real robot system are conducted, which demonstrate the proposed method has competitive performance in random moving object tracking and grasping.