Liangbai Liu — accepted AI-conference papers

2026

LeGO-MM: Learning Navigation for Goal-Oriented Mobile Manipulation Via Hierarchical Policy Distillation

Bolei Chen, Liangbai Liu, Shengsheng Yan, Haonan Yang, Ping Zhong, Jianxin Wang

ICRA 2026poster

Benefiting from mobility and dexterity, Mobile Manipulation (MM) systems are expected to assist humans with diverse tasks in everyday life. However, since MM tasks (e.g., tidying up a room) require learning multi-stage heterogeneous behaviors (e.g., picking, placing, and opening), existing Reinforce…

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2026

Spatially Generalizable Mobile Manipulation via Adaptive Experience Selection and Dynamic Imagination

Ping Zhong, Liangbai Liu, Bolei Chen, Tao Wu, Jiazhi Xia, Chaoxu Mu +1

IJCAI 2026

Mobile Manipulation (MM) involves long-horizon decision-making over multi-stage compositions of heterogeneous skills, such as navigation and picking up objects. Despite recent progress, existing MM methods still face two key limitations: (i) low sample efficiency, due to ineffective use of redundant

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