Meng Guo
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Meng Guo (国萌) |
Research Interest
My general research interest is task and motion planning for robots, particularly in two domains: (1) distributed and hybrid control of interconnected multi-robot systems under complex goals; (2) skill learning and planning of robotic manipulators.
It is an interdisciplinary area between continuous motion control and discrete planning, under various constraints such as timing or resource limits and geometric or dynamic properties. Currently, I investigate how to combine data-driven methods with model-based formulations to improve data efficiency and online performance.
More about my research and GitHub page.
We are constantly looking for Summer interns, Bachelor thesis, PhD candidates, PostDocs to join CoE, PKU.
News
June 16: Four IROS25 papers accepted:
LOMORO: Long-term Monitoring of Dynamic Targets with Minimum Robotic Fleet under Resource Constraints, Mingke Lu, Shuaikang Wang, Meng Guo.
Multi-UAV Deployment in Obstacle-Cluttered Environments with LOS Connectivity, Yuda Chen, Shuaikang Wang, Jie Li, Meng Guo.
DEXTER-LLM: Dynamic and Explainable Coordination of Multi-Robot Systems in Unknown Environments via Large Language Models, Yuxiao Zhu, Junfeng Chen, Xintong Zhang, Meng Guo*, Zhongkui Li.
Homotopy-aware Multi-agent Navigation via Distributed Model Predictive Control, Haoze Dong, Meng Guo, Chengyi He, Zhongkui Li.
May. 23: ICRA25 Keynote talk on Safety & Formal Methods.
Jan. 30: Two ICRA25 papers accepted:
FlyKites: Human-centric Interactive Exploration and Assistance under Limited Communication, Yuyang Zhang, Zhuoli Tian, Jinsheng Wei and Meng Guo.
HULK: Large-scale Hierarchical Coordination under Continual and Uncertain Temporal Tasks, Qingyuan Luo, Jie Li and Meng Guo.
Jan. 8: Checkout lastest work on Hybrid and Oriented Harmonic Potentials for Safe Task Execution in Unknown Environment on Automatica. [PDF][Website]