2023-08-29 カーネギーメロン大学
Researchers in the School of Computer Science have developed a robotic system that helps humans dress and accommodates various body shapes, arm poses and clothing selections.
◆このシステムは、AIの能力を活用し、異なる体形や腕のポーズ、衣類に適応することができる。強化学習を使用して、ロボットに衣類を適切に装着する方法を学習させ、その成功率を向上させた。シミュレーションを通じてロボットに衣服の操作方法を教え、実世界へ適応させる際に衣類の特性を考慮しました。人間のスタディでシステムを評価し、多くの参加者の大部分に対して成功を収め、将来的にはより複雑なタスクへの展開や、ユーザーの動きに適応する能力を向上させることが目指されています。
＜関連情報＞
1つのポリシーですべてを着こなす：多様なポーズと衣服を持つ人々に服を着せることを学ぶ
One Policy to Dress Them All: Learning to Dress People with Diverse Poses and Garments
Yufei Wang, Zhanyi Sun, Zackory Erickson, David Held
arXiv Submitted on 21 Jun 2023
DOI:https://doi.org/10.48550/arXiv.2306.12372
Robot-assisted dressing could benefit the lives of many people such as older adults and individuals with disabilities. Despite such potential, robot-assisted dressing remains a challenging task for robotics as it involves complex manipulation of deformable cloth in 3D space. Many prior works aim to solve the robot-assisted dressing task, but they make certain assumptions such as a fixed garment and a fixed arm pose that limit their ability to generalize. In this work, we develop a robot-assisted dressing system that is able to dress different garments on people with diverse poses from partial point cloud observations, based on a learned policy. We show that with proper design of the policy architecture and Q function, reinforcement learning (RL) can be used to learn effective policies with partial point cloud observations that work well for dressing diverse garments. We further leverage policy distillation to combine multiple policies trained on different ranges of human arm poses into a single policy that works over a wide range of different arm poses. We conduct comprehensive real-world evaluations of our system with 510 dressing trials in a human study with 17 participants with different arm poses and dressed garments. Our system is able to dress 86% of the length of the participants’ arms on average. Videos can be found on our project webpage: this https URL.
