【摘要】 在采用机器人进行远程操作过程中，针对任务空间映射算法的参数确定缺少系统化理论的问题，提出了一种系统化的定缩放因子映射算法和姿态映射算法，使映射后的人臂工作空间尽可能充满机械臂工作空间；针对任务空间映射会丢失臂型角信息的问题，提出基于黄金分割法的臂型角逆运动学求解方法，将臂型角的概念推广到有连杆长度的SRS型机械臂中；针对Kinect相机的随机抖动，提出基于卡尔曼滤波的消抖算法。实验结果表明：逆运动学算法能以平均时间2.8 ms正确跟踪期望轨迹；轨迹跟踪x方向平均误差为9.04 mm,y方向误差为10.49 mm,z方向误差为6.49 mm,臂型角平均跟踪误差为0.74°。Baxter机械臂能够执行期望的目标轨迹，并能够根据人臂的臂型角调整构形。更多还原

【Abstract】 For the applications of robotic remote control, the systematic theory is lacking in parameter determination of task space mapping algorithm. In this paper, a systematic fixed scaling factor mapping algorithm and orientation mapping algorithm was proposed to make the mapped human hand workspace filling the manipulator workspace as much as possible. To solve the problem of missing arm angle information in task space mapping, an inverse kinematics method based on golden section method was presented. The concept of arm angle was successfully extended to SRS(Spherical-Roll-Spherical) robotic arm with link length, like Baxter. Finally, to reduce the random jitter of Kinect camera, an algorithm based on Kalman filter was proposed. Experiments showed that the inverse kinematics algorithm could track the desired trajectory correctly with the average time of 2.8 ms. Baxter manipulator could track the desired end effector trajectory with the average error of 9.04 mm along x direction, 10.49 mm error along y direction, and 6.49 mm error along z direction. Moreover, the manipulator could change the configuration adaptively based on human arm angle with the average tracking error of 0.74°.更多还原