ICRA 2024 - Cloth Competition

The ICRA 2024 Cloth Competition, held as part of the 9th RGMC, focused on grasp point localization for robotic cloth unfolding. Eleven teams competed with their perception systems on a standardized dual-arm robot setup, with evaluations conducted live at ICRA 2024 in Yokohama, Japan.

This competition resulted in a comprehensive dataset of robotic cloth unfolding attempts, capturing valuable real-world data across diverse garments. The dataset is a key resource for developing and evaluating new algorithms for cloth manipulation.

A paper describing the competition and the dataset was submitted to the International Journal of Robotics Research (IJRR) for review.

Left: Dual UR5e setup we will provide at ICRA 2024. Right: Grasp point localisation on a hanging shirt.

Important links

Highlights

Competition Ranking πŸ†

Congratulations to all 11 teams who successfully completed their 16 live evaluation trials in the ICRA 2024 Cloth Competition! We’re proud of the hard work and dedication each team put into this challenge. The final rankings and scores are listed below.

Rank Team Name Score (Average Coverage)
πŸ₯‡ 1st AIR-JNU 0.60
πŸ₯ˆ 2nd Team Ljubljana 0.57
πŸ₯‰ 3rd Ewha Glab 0.55
4th SCUT-ROBOT 0.53
5th Team Greater Bay 0.53
6th Samsung Research China - Beijing 0.48
7th Shibata Lab 0.46
8th AI&ROBOT LAB 0.45
9th UOS-Robotics 0.39
10th AIS Shinshu 0.37
11th 3C1S 0.35

Open Source Code from Participants

The following teams have already generously shared their code:

Team Name Code Repository
EWHA GLab https://github.com/minseo10/cloth_unfolding
Team Ljubljana https://github.com/vicoslab/CeDiRNet

The Challenge

Regrasping garments in the air is a popular cloth unfolding strategy. To get started, it’s common to grasp the lowest point. However, better grasp points are needed to unfold the garment completely, such as the shoulders of a shirt or the waist of shorts. The objective of the competition is to localise good grasp poses in colour and depth images of garments held in the air by one gripper. We will evaluate your predicted grasp by executing it on a dual UR5e setup live at ICRA. The cloth items that must be grasped will be towels, shirts and shorts. We will provide an image dataset of representative cloth items for preparation, but the evaluation will also include unseen garments.

Practicalities

Participants do not have to worry about the initial lifting of the cloth, grasp execution, camera calibration, etc. We will take care of all that with our open-source codebase airo-mono! At the competition, we will send you an image and you just send us a grasp back in a to-be-specified JSON format. Together with the dataset, we will also provide a Github repository with notebooks and tools to load, visualise and explore the data. Don’t hesitate to contact us if you have any questions!

Teams

UOS-Robotics

  • Uihun Sagong
  • JungHyun Choi
  • JeongHyun Park
  • Dongwoo Lee
  • Yeongmin Kim

Ewha Glab

  • Hyojeong Yu
  • Minseo Kwon

AI&ROBOT LAB

  • Chongkun Xia
  • Kai Mo
  • Yanzhao Yu
  • Qihao Lin
  • Binqiang Ma

3C1S

  • Carlos Mateo-Agullo

Shibata Lab

  • Kakeru Yamasaki
  • Tomohiro Shibata
  • Krati Saxena
  • Takumi Kajiwara
  • Yuki Nakadera

AIS Shinshu

  • Solvi Arnold
  • Kimitoshi Yamazaki
  • Daisuke Tanaka
  • Keisuke Onda
  • Akihisa Ishikawa
  • Yusuke Kuribayashi
  • Naoki Hiratsuka

Team Greater Bay

  • Fang Wan
  • Linhan Yang
  • Haoran Sun
  • Ning Guo
  • Chaoyang Song
  • Jia Pan
  • Lei Yang
  • Zeqing Zhang

Team Ljubljana

  • Domen Tabernik
  • Andrej Gams
  • Peter Nimac
  • Matej Urbas
  • Jon Muhovič
  • Danijel Skočaj
  • Matija Mavsar

SCUT-ROBOT

  • Supeng Diao
  • Yang Cong
  • Yu Ren
  • Ronghan Chen
  • Jiawei Weng
  • Jiayue Liu

Air-jnu

  • Giwan Lee
  • Jiyoung Choi
  • Jeongil Choi
  • Geon Kim
  • Phayuth Yonrith

Samsung Research China – Beijing

  • Yixiang Jin
  • Dingzhe Li
  • Yong A
  • Jun Shi
  • Yong Yang

Contact

Partners