# Dynamic Movement Primitive based Motion Retargeting for Dual-Arm Sign Language Motions

arXiv: https://arxiv.org/abs/2011.03914 · HTML: https://mlsanity.com/paper/2011.03914/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Nov 2020.

## Built on by (most cited first, 6 of 6)

- [OKAMI: Teaching Humanoid Robots Manipulation Skills through Single Video Imitation](https://mlsanity.com/paper/2410.11792/) (2024)
- [Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations](https://mlsanity.com/paper/2507.00990/) (2025)
- [MASA: Motion-aware Masked Autoencoder with Semantic Alignment for Sign Language Recognition](https://mlsanity.com/paper/2405.20666/) (2024)
- [Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning](https://mlsanity.com/paper/2307.16062/) (2023)
- [GBC: Generalized Behavior-Cloning Framework for Whole-Body Humanoid Imitation](https://mlsanity.com/paper/2508.09960/) (2025)
- [Bridging the Communication Gap: Artificial Agents Learning Sign Language through Imitation](https://mlsanity.com/paper/2406.10043/) (2024)

## Abstract (arXiv)

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.