Zheng Shen — accepted AI-conference papers

2025

LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks

Kejia Chen, Zheng Shen, Yue Zhang, Lingyun Chen, Fan Wu, Zhenshan Bing +2

ICRA 2025

Large Language Models (LLMs) have gained popularity in task planning for long-horizon manipulation tasks. To enhance the validity of LLM-generated plans, visual demonstrations and online videos have been widely employed to guide the planning process. However, for manipulation tasks involving subtle

Cited by 2 Source ↗code ↗Scholar ↗

2024

Safe Execution of Learned Orientation Skills with Conic Control Barrier Functions

Zheng Shen, Matteo Saveriano, Fares J. Abu-Dakka, Sami Haddadin

ICRA 2024poster

In the field of Learning from Demonstration (LfD), Dynamical Systems (DSs) have gained significant attention due to their ability to generate real-time motions and reach predefined targets. However, the conventional convergence-centric behavior exhibited by DSs may fall short in safety-critical task…

Cited by 1 Source ↗Scholar ↗