  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.
