Contributions

List of Accepted Abstracts

No   Title and Authors 


  1              Purely Vision-Based Robotic Grasping in Clutter with Parallel Jaw

                   Shihefeng Wang, Weiduo Gong, Yingyue Li, Junqi Ge, and Xiang Li


  2              Overcoming Heavy Clutter: Utilizing the Hybrid Grasping Network and Gripper

                   Seunghwan Um, Yeong Gwang Son, Tat Hieu Bui, Ho Sang Jung, and Hyouk Ryeol Choi


  3              Contact-Implicit Model Predictive Control for Dexterous In-hand Manipulation: A Long-Horizon and Robust Approach

                   Yongpeng Jiang, Mingrui Yu, Xinghao Zhu, Masayoshi Tomizuka, and Xiang Li


  4              Object Extreme Points Detection and Flexible Grasp Pose Solution for Human-to-Robot Handover Competition

                   Phayuth Yonrith, Jiyoung Choi, Jeongil Choi, Geon Kim, Giwan Lee and Ayoung Hong


  5              A Cluttered Object-grasping Framework Based on a Multifunctional Soft Gripper

                   Xiankun Zhu, Yucheng Xin, Xianru Tian, Shoujie Li, Xueqian Wang


  6              The DARRL Dataset: A Collection of Human Manipulation Tasks for Action Recognition, Video Object Segmentation and Robotic Learning from Demonstration

                   Mathieu Riand, Patrick Le Callet, and Laurent Doll´e


  7              CopGNN: Learning End-to-End Cloth Coverage Prediction via Graph Neural Networks

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


  8              In-Hand Following of Deformable Linear Objects Using Dexterous Fingers with Tactile Sensing

                   Mingrui Yu, Boyuan Liang, Xiang Zhang, Xinghao Zhu, Lingfeng Sun, Changhao Wang, Shiji Song, Xiang Li, and Masayoshi Tomizuka


  9              Grasp Point Detection for Cloth Manipulation with CeDiRNet-6DoF

                   Domen Tabernik, Peter Nimac, Matija Mavsar, Jon Muhoviˇc, Matej Urbas, Andrej Gams, and Danijel Skoˇcaj


 10            Vine-like, Power Soft Gripper with the Pop-up Structure

                   Hiroto Kodama, Tohru Ide, Yunhao Feng, Hiroyuki Nabae, and Koichi Suzumori


Purely Vision-Based Robotic Grasping in Clutter with Parallel Jaw_final.pdf

Purely Vision-Based Robotic Grasping in Clutter with Parallel Jaw

Shihefeng Wang, Weiduo Gong, Yingyue Li, Junqi Ge, and Xiang Li


[ paper | video ]

Overcoming Heavy Clutter: Utilizing the Hybrid Grasping Network and Gripper

Seunghwan Um, Yeong Gwang Son, Tat Hieu Bui, Ho Sang Jung, and Hyouk Ryeol Choi


[ paper | video ]

Overcoming Heavy Clutter Utilizing the Hybrid Grasping Network and Gripper_final.pdf
Contact-Implicit Model Predictive Control for Dexterous In-hand Manipulation A Long-Horizon and Robust Approach_final.pdf

Contact-Implicit Model Predictive Control for Dexterous In-hand Manipulation: A Long-Horizon and Robust Approach

Yongpeng Jiang, Mingrui Yu, Xinghao Zhu, Masayoshi Tomizuka, and Xiang Li


[ paper ]

 Object Extreme Points Detection and Flexible Grasp Pose Solution for Human-to-Robot Handover Competition

Phayuth Yonrith, Jiyoung Choi, Jeongil Choi, Geon Kim, Giwan Lee and Ayoung Hong


[ paper ]

Object Extreme Points Detection and Flexible Grasp Pose Solution for Human-to-Robot Handover Competition_final.pdf
A Cluttered Object-grasping Framework Based on a Multifunctional Soft Gripper_final.pdf

A Cluttered Object-grasping Framework Based on a Multifunctional Soft Gripper

Xiankun Zhu, Yucheng Xin, Xianru Tian, Shoujie Li, Xueqian Wang


[ paper | video ]

The DARRL Dataset: A Collection of Human Manipulation Tasks for Action Recognition, Video Object Segmentation and Robotic Learning from Demonstration

Mathieu Riand, Patrick Le Callet, and Laurent Doll´e


[ paper ]

The DARRL Dataset_final.pdf
CopGNN Learning End-to-End Cloth Coverage Prediction via Graph Neural Networks_final.pdf

CopGNN: Learning End-to-End Cloth Coverage Prediction via Graph Neural Networks

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


[ paper ]

In-Hand Following of Deformable Linear Objects Using Dexterous Fingers with Tactile Sensing

Mingrui Yu, Boyuan Liang, Xiang Zhang, Xinghao Zhu, Lingfeng Sun, Changhao Wang, Shiji Song, Xiang Li, and Masayoshi Tomizuka


[ paper | video ]

In-Hand Following of Deformable Linear Objects Using Dexterous Fingers with Tactile Sensing_final.pdf
Grasp Point Detection for Cloth Manipulation with CeDiRNet-6DoF_final.pdf

Grasp Point Detection for Cloth Manipulation with CeDiRNet-6DoF

Domen Tabernik, Peter Nimac, Matija Mavsar, Jon Muhoviˇc, Matej Urbas, Andrej Gams, and Danijel Skoˇcaj


[ paper ]

Vine-like, Power Soft Gripper with the Pop-up Structure

 Hiroto Kodama, Tohru Ide, Yunhao Feng, Hiroyuki Nabae, and Koichi Suzumori


[ paper | video ]

Vine-like Power Soft Gripper with the Pop-up Structure_final.pdf

Call for Extended Abstracts

We invite interested authors to submit extended abstracts (2 pages) of relevant works that will be peer-reviewed. Accepted abstracts will be posted on the workshop website and can be presented during the poster session of the workshop. The best extended abstract will have the chance to give a talk during the main event of the workshop. In addition, we are planning to organize a journal special issue, and selected extended abstracts will be invited for submission.

All submissions should be in the form of a single PDF in IROS format (LaTex or Word).  Submissions will be handled through the following MCT page: https://cmt3.research.microsoft.com/IROSworkshop2024.

Topics of interest for the extended abstract include, but are not limited to: 

Important dates (anywhere on Earth)