@workshop{Sun2024CopGNN,

title = {CopGNN: Learning End-to-End Cloth Coverage Prediction via Graph Neural Networks},

author = {Haoran Sun and Linhan Yang and Zeqing Zhang and Ning Guo and Lei Yang and Fang Wan and Chaoyang Song and Jia Pan},

url = {https://sites.google.com/view/iros2024-workshop-bench-in-rgm/},

year  = {2024},

date = {2024-10-13},

urldate = {2024-10-13},

abstract = {Cloth manipulation in robotics, such as folding or unfolding fabrics, remains challenging due to deformable materials' complex and nonlinear dynamics, which can adopt infinite configurations. As Team Greater Bay, we participated in the ICRA 2024 Cloth Competition and scored an Average Coverage of 0.53 (the 1st place team scored 0.60). This extended abstract presents our Coverage Prediction Graph Neural Network (CopGNN) approach implemented for this competition. Instead of directly estimating the cloth's configuration, our method implicitly infers the unknown state using a Graph Neural Network (GNN). It predicts the resultant coverage area from multiple grasping points using a second GNN without relying on an explicit dynamics model. Contributions of this work include: (1) Developed a comprehensive simulation pipeline to generate a large-scale dataset tailored to the cloth manipulation task. (2) Proposed an end-to-end approach to predict the coverage area using only the hanging cloth's depth image. (3) Introduced a heuristic-based sampling strategy to enhance the robustness of zero-shot sim-to-real transfer.},

note = {Extended Abstract accepted to IROS 2024 Workshop on Benchmarking via Competitions in Robotic Grasping and Manipulation},

keywords = {},

pubstate = {published},

tppubtype = {workshop}

}

@workshop{Wu2024MagiClaw,

title = {From DeepClaw to MagiClaw: Towards Universal Action Embodiment},

author = {Tianyu Wu and Sheng Ge and Yujian Dong and Ronghan Xu and Fang Wan and Chaoyang Song},

url = {https://edmws.github.io/},

year  = {2024},

date = {2024-10-13},

urldate = {2024-10-13},

note = {Extended Abstract accepted to IROS 2024 Workshop on Environment Dynamics Matters: Embodied Navigation to Movable Objects},

keywords = {},

pubstate = {published},

tppubtype = {workshop}

}

@workshop{Luo2020MappingHuman,

title = {Mapping Human Muscle Force to Supernumerary Robotics Device for Overhead Task Assistance},

author = {Jianwen Luo and Sicong Liu and Chengyu Lin and Yong Zhou and Zixuan Fan and Zheng Wang and Chaoyang Song and Harry Asada and Chenglong Fu},

url = {https://aim2020srd.wixsite.com/aim2020srd},

doi = {10.48550/arXiv.2107.13799},

year  = {2020},

date = {2020-11-01},

urldate = {2020-11-01},

note = {Extended Abstract accepted to the IEEE/ASME AIM 2020 Workshop on Supernumerary Robotic Devices},

keywords = {},

pubstate = {published},

tppubtype = {workshop}

}