论文标题
双臂手语动作的动态运动原始运动重新定位
Dynamic Movement Primitive based Motion Retargeting for Dual-Arm Sign Language Motions
论文作者
论文摘要
我们旨在开发一种有效的编程方法，用于将服务机器人与执行手语动作的技巧相准备。本文解决了转移复杂的复杂双臂手语动作的问题，其特征在于手臂和手之间的协调，从人到机器人，这在先前的运动重新定位技术研究中很少考虑。在本文中，我们提出了一种新型的运动重新定位方法，该方法利用图形优化和动态运动原语（DMP）来解决此问题。我们以领导者的方式采用DMP来参数化原始轨迹，同时保持运动节奏和人体部位之间的相对运动，并采用三步优化程序，以找到用于机器人运动计划的变形轨迹，同时确保机器人执行的可行性。几种中文手语（CSL）动作的实验结果已在ABB的Yumi双臂协作机器人（14-DOF）上成功执行，并具有两个6-DOF Inspire-bobotics的多指手指，这是一个总共26个DOF的系统。
We aim to develop an efficient programming method for equipping service robots with the skill of performing sign language motions. This paper addresses the problem of transferring complex dual-arm sign language motions characterized by the coordination among arms and hands from human to robot, which is seldom considered in previous studies of motion retargeting techniques. In this paper, we propose a novel motion retargeting method that leverages graph optimization and Dynamic Movement Primitives (DMPs) for this problem. We employ DMPs in a leader-follower manner to parameterize the original trajectories while preserving motion rhythm and relative movements between human body parts, and adopt a three-step optimization procedure to find deformed trajectories for robot motion planning while ensuring feasibility for robot execution. Experimental results of several Chinese Sign Language (CSL) motions have been successfully performed on ABB's YuMi dual-arm collaborative robot (14-DOF) with two 6-DOF Inspire-Robotics' multi-fingered hands, a system with 26 DOFs in total.
