Junting Chen

Ph.D. in Computer Science with President Graduate Fellowship (PGF)

National University of Singapore

Hi, this is Junting Chen (陈俊廷), currently a CS Ph.D. student at the National University of Singapore (NUS), advised by Prof. Lin Shao. Before that, he was a student researcher at Shanghai Artificial Intelligence Lab in Embodied AI and robotic systems, working with Yao Mu and Ping Luo. He earned his master’s degree in Robotics and Artificial Intelligence at ETH Zurich, with Prof. Luc Van Gool as master’s program tutor. At ETH Zurich, he worked with Dr. Suryansh Kumar and Dr. Guohao Li at CVL. Before that, he earned my BSc in Computer Science at the University of Chinese Academy of Sciences, working with Prof. Ruiping Wang and Xilin Chen during his undergraduate studies.

My current research interest is the gap between the perception and action in indoor-scene Embodied AI: 1) How to construct a unified scene representation during active exploration that supports multiple high-level embodied tasks. 2) How to make long-term decisions and predict instant actions conditioned on different intentions by leveraging the information in the scene representation and common sense knowledge.

I (and my lab) am actively recruiting intern students on-site (Singapore/ Shenzhen, China) or online. Please send me your proposal and resume for internship application. Besides, I am open to any form of discussion/ cooperation, please drop me email.

selected publications

RSS

How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers

embodied-ai navigation

Junting Chen, Guohao Li, Suryansh Kumar, and 2 more authors

In Proceedings of Robotics: Science and Systems (RSS), 2023

Abs DOI arXiv Video Website

Object goal navigation is an important problem in Embodied AI that involves guiding the agent to navigate to an instance of the object category in an unknown environment—typically an indoor scene. We present a modular and training-free solution, which embraces more classic approaches, to tackle the object goal navigation problem. Our method builds a structured scene representation based on classic visual simultaneous localization and mapping (V-SLAM) framework and reasons about promising areas to search goal object by injecting semantics to geometric-based frontier exploration.
arXiv

RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation

embodied-ai LLM manipulation

Junting Chen, Yao Mu, Qiaojun Yu, and 11 more authors

2024

Abs arXiv

We present RoboScript, a code generation framework for free-form manipulation tasks across both real and simulated environments.
arXiv

RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis

embodied-ai VLM manipulation

Yao Mu, Junting Chen, Qinglong Zhang, and 16 more authors

2024

Abs arXiv

We present RoboCodeX, a multimodal code generation framework for robotic behavior synthesis.
EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents

llm multi-agent embodied-ai

Junting Chen, Checheng Yu, Xunzhe Zhou, and 7 more authors

In The Thirteenth International Conference on Learning Representations (ICLR), 2025

Abs Website

We present EMOS, an embodiment-aware heterogeneous multi-robot operating system powered by large language model (LLM) agents.
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis

mobile-manipulation embodied-ai vlm

Junting Chen, Haotian Liang, Lingxiao Du, and 8 more authors

In Advances in Neural Information Processing Systems (NeurIPS), 2025

Abs Website

We present OWMM-Agent, a framework for open world mobile manipulation with multi-modal agentic data synthesis.
LISN: Language-Instructed Social Navigation with VLM-based Controller Modulating

navigation embodied-ai vlm

Junting Chen, Yunchuan Li, Panfeng Jiang, and 5 more authors

2025

Abs Website

We present the first simulation benchmark LISN-Bench for language instructed socially navigation benchmark with human-robot coexistence and high environment dynamic, and the fast-slow hierarchical system Social-Nav-Modulator to tackle the introduced social navigation tasks.