Chenchang Li — accepted AI-conference papers

2024

DeformNet: Latent Space Modeling and Dynamics Prediction for Deformable Object Manipulation

Chenchang Li, Zihao Ai, Tong Wu, Xiaosa Li, Wenbo Ding, Huazhe Xu

ICRA 2024poster

Manipulating deformable objects is a ubiquitous task in household environments, demanding adequate representation and accurate dynamics prediction due to the objects’ infinite degrees of freedom. This work proposes DeformNet, which utilizes latent space modeling with a learned 3D representation mode…

Cited by 6 Source ↗Scholar ↗

2024

Dual-modal Tactile E-skin: Enabling Bidirectional Human-Robot Interaction via Integrated Tactile Perception and Feedback

Shilong Mu, Runze Zhao, Zenan Lin, Yan Huang, Shoujie Li, Chenchang Li +2

ICRA 2024poster

To foster an immersive and natural human-robot interaction (HRI), the implementation of tactile perception and feedback becomes imperative, effectively bridging the conventional sensory gap. In this paper, we propose a dual-modal electronic skin (e-skin) that integrates magnetic tactile sensing and…

Cited by 2 Source ↗Scholar ↗