Yenan Chen — accepted AI-conference papers

2025

Disambiguate Gripper State in Grasp-Based Tasks: Pseudo-Tactile as Feedback Enables Pure Simulation Learning

Yifei Yang, Lu Chen, Zherui Song, Yenan Chen, Wentao Sun, Zhongxiang Zhou +2

IROS 2025

Grasp-based manipulation tasks are fundamental to robots interacting with their environments, yet gripper state ambiguity significantly reduces the robustness of imitation learning policies for these tasks. Data-driven solutions face the challenge of high real-world data costs, while simulation data

Cited by 2 Source ↗Scholar ↗

2022

Scalable Simulation and Demonstration of Jumping Piezoelectric 2-D Soft Robots

Zhiwu Zheng, Prakhar Kumar, Yenan Chen, Hsin Cheng, Sigurd Wagner, Minjie Chen +2

ICRA 2022poster

Soft robots have drawn great interest due to their ability to take on a rich range of shapes and motions, compared to traditional rigid robots. However, the motions, and underlying statics and dynamics, pose significant challenges to forming well-generalized and robust models necessary for robot des…

Cited by 12 Source ↗code ↗Scholar ↗