Welding seam tracking precision was decreased due to human hand tremor during the master-slave welding teleoperation. To solve this problem, a master-slave robot remote welding system was built, the system consisted o...Welding seam tracking precision was decreased due to human hand tremor during the master-slave welding teleoperation. To solve this problem, a master-slave robot remote welding system was built, the system consisted of a master manipulator with six degree of freedom （ DOF ） , an industrial computer control system and a slave Motoman HP3 J robot, and human hand tremor and digital filtering were discussed. An optimal digital filter was designed to clean human tremor signal for improving the welding seam tracking precision. The experimental results show that the digital filter suppresses the operator＇ s tremor signal.展开更多
为了在视域(field of view,FOV)不同的条件下实现对数量时变的不确定目标的最优跟踪,提出一种高斯混合概率假设密度(Gaussian mixture probability hypothesis density,GM-PHD)滤波器的去相关算术平均(arithmetic average,AA)融合算法...为了在视域(field of view,FOV)不同的条件下实现对数量时变的不确定目标的最优跟踪,提出一种高斯混合概率假设密度(Gaussian mixture probability hypothesis density,GM-PHD)滤波器的去相关算术平均(arithmetic average,AA)融合算法。鉴于多目标AA融合被分解为多组单目标分量的合并,先通过重构贝叶斯融合推导出最优去相关估计融合,后将其用作单目标分量的合并方法。由于推导的去相关估计融合需要先验估计,设计了一个包含主滤波器的分层结构,以自动提供需要的先验估计。为了解决不同FOV导致的目标势低估问题,融合节点利用FOV补偿单目标分量的权重。仿真结果证实了提出的算法在各种场景中的最优性,提升了多目标跟踪的精度。展开更多
基金This research is supported by National Natural Science Foundation of China （No. 50905043）.
文摘Welding seam tracking precision was decreased due to human hand tremor during the master-slave welding teleoperation. To solve this problem, a master-slave robot remote welding system was built, the system consisted of a master manipulator with six degree of freedom （ DOF ） , an industrial computer control system and a slave Motoman HP3 J robot, and human hand tremor and digital filtering were discussed. An optimal digital filter was designed to clean human tremor signal for improving the welding seam tracking precision. The experimental results show that the digital filter suppresses the operator＇ s tremor signal.
文摘为了在视域(field of view,FOV)不同的条件下实现对数量时变的不确定目标的最优跟踪,提出一种高斯混合概率假设密度(Gaussian mixture probability hypothesis density,GM-PHD)滤波器的去相关算术平均(arithmetic average,AA)融合算法。鉴于多目标AA融合被分解为多组单目标分量的合并,先通过重构贝叶斯融合推导出最优去相关估计融合,后将其用作单目标分量的合并方法。由于推导的去相关估计融合需要先验估计,设计了一个包含主滤波器的分层结构,以自动提供需要的先验估计。为了解决不同FOV导致的目标势低估问题,融合节点利用FOV补偿单目标分量的权重。仿真结果证实了提出的算法在各种场景中的最优性,提升了多目标跟踪的精度。
