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
Nov. 8: Checkout lastest work on Hybrid and Oriented Harmonic Potentials for Safe Task Execution in Unknown Environment on Automatica. [PDF][Website]
May. 14: Two RSS24 papers accepted:
May. 12: Gonna have a strong presence at ICRA24:
Spotlight talk and poster at HERMES workshop.
Best paper finalist talk at TuCA2-CC.4 for Multi-Robots Systems.
RAL oral presentation at WeCT4-CC.5 for Distributed Robot Systems.
Flash talk and poster at Breaking Swarm Stereotypes workshop.
Apr. 8: Checkout our ECC24 workshop on Task and Motion Coordination under Geometric, Dynamic and Temporal Constraints (TMC+X).
Jan. 30: Checkout our ICRA24 paper on Uncertainty-bounded Active Monitoring of Unknown Dynamic Targets in Road-networks with Minimum Fleet.