重力补偿算法需要实时估计力传感器的初始值及工具重力对力传感器所施加的力和力矩,进而获得外界所施加的力和力矩。当估计工具重力对力传感器所施加的力和力矩时,需要获得力传感器坐标系和机器人末端坐标系的旋转变换矩阵。当前的重力...重力补偿算法需要实时估计力传感器的初始值及工具重力对力传感器所施加的力和力矩,进而获得外界所施加的力和力矩。当估计工具重力对力传感器所施加的力和力矩时,需要获得力传感器坐标系和机器人末端坐标系的旋转变换矩阵。当前的重力补偿算法采用手动校准的方式,通过不断的拆卸力传感器去保证力传感器坐标系和机器人末端坐标系平行。该手动校准的方式操作复杂耗时较长,本文提出一种带有标定力传感器坐标系相对于机器人末端坐标系的重力补偿算法,从算法层面标定力传感器坐标系和机器人末端坐标系的旋转变换矩阵,实现重力补偿算法的自动化。通过实验验证该方法不需要手动校准,即可实现[0.237/N 0.395/N 0.928/N 0.032/N·m 0.018/N·m 0.002/N·m]的重力补偿误差。The gravity compensation algorithm requires real-time estimation of the initial values of the force sensor and the forces and torques applied by the tool’s gravity on the force sensor. This allows us to obtain the external forces and torques. When estimating the forces and torques applied by the tool’s gravity on the force sensor, the rotation transformation matrix between the force sensor frame and the robot’s end-effector frame is needed. The current gravity compensation algorithm uses manual calibration, involving repeated disassembly of the force sensor to ensure that the frame of the force sensor and the robot’s end-effector are parallel. This manual process is complex and time-consuming. This paper proposes a gravity compensation algorithm that calibrates the rotation transformation matrix between the force sensor and the robot’s end-effector frame through the algorithm, automating the gravity compensation process. Experimental results show that this method achieves a gravity compensation error of [0.237/N 0.395/N 0.928/N 0.032/N·m 0.018/N·m 0.002/N·m] without manual calibration.展开更多
脑静脉窦血栓形成（cerebral venous and sinus thrombosis,CVST）是一种相当少见的疾病,〈所有卒中的1%。目前在临床实践中采取的治疗措施包括抗凝、溶栓和对症治疗。本文作者分析20例经DSA确诊的CVST患者,并行静脉窦置管溶栓治疗。作...脑静脉窦血栓形成（cerebral venous and sinus thrombosis,CVST）是一种相当少见的疾病,〈所有卒中的1%。目前在临床实践中采取的治疗措施包括抗凝、溶栓和对症治疗。本文作者分析20例经DSA确诊的CVST患者,并行静脉窦置管溶栓治疗。作者所提供的资料真实可靠,相关数据显示其治疗效果显效率为80%,有效率为95%,说明此治疗方法对CVST行之有效。展开更多
文摘重力补偿算法需要实时估计力传感器的初始值及工具重力对力传感器所施加的力和力矩,进而获得外界所施加的力和力矩。当估计工具重力对力传感器所施加的力和力矩时,需要获得力传感器坐标系和机器人末端坐标系的旋转变换矩阵。当前的重力补偿算法采用手动校准的方式,通过不断的拆卸力传感器去保证力传感器坐标系和机器人末端坐标系平行。该手动校准的方式操作复杂耗时较长,本文提出一种带有标定力传感器坐标系相对于机器人末端坐标系的重力补偿算法,从算法层面标定力传感器坐标系和机器人末端坐标系的旋转变换矩阵,实现重力补偿算法的自动化。通过实验验证该方法不需要手动校准,即可实现[0.237/N 0.395/N 0.928/N 0.032/N·m 0.018/N·m 0.002/N·m]的重力补偿误差。The gravity compensation algorithm requires real-time estimation of the initial values of the force sensor and the forces and torques applied by the tool’s gravity on the force sensor. This allows us to obtain the external forces and torques. When estimating the forces and torques applied by the tool’s gravity on the force sensor, the rotation transformation matrix between the force sensor frame and the robot’s end-effector frame is needed. The current gravity compensation algorithm uses manual calibration, involving repeated disassembly of the force sensor to ensure that the frame of the force sensor and the robot’s end-effector are parallel. This manual process is complex and time-consuming. This paper proposes a gravity compensation algorithm that calibrates the rotation transformation matrix between the force sensor and the robot’s end-effector frame through the algorithm, automating the gravity compensation process. Experimental results show that this method achieves a gravity compensation error of [0.237/N 0.395/N 0.928/N 0.032/N·m 0.018/N·m 0.002/N·m] without manual calibration.
文摘脑静脉窦血栓形成（cerebral venous and sinus thrombosis,CVST）是一种相当少见的疾病,〈所有卒中的1%。目前在临床实践中采取的治疗措施包括抗凝、溶栓和对症治疗。本文作者分析20例经DSA确诊的CVST患者,并行静脉窦置管溶栓治疗。作者所提供的资料真实可靠,相关数据显示其治疗效果显效率为80%,有效率为95%,说明此治疗方法对CVST行之有效。
