3 papers indexed
Yi Li, Alexandre Chapin, Liming Chen, Jan Peters, Alap Kshirsagar
Robotic manipulation policies rely on pre-trained vision models that give either a global scene embedding or a dense patch grid. Both mix task-relevant and task-irrelevant features. Object-centric slot representations are a structured alternative: they group features into a few p…
Zezeng Li, Enda Xiang, Thuy Tran, Di Huang, Momath Thiam, Liming Chen
Imitation learning has enabled remarkable progress in robotic manipulation, especially with diffusion and flow-based policies that generate complex visuomotor behaviors directly from demonstrations. Yet, despite their strong performance, these policies often fail to generalize ac…
Jintao Kong, Zhihao Zhang, Weihuang Chen, Liming Chen, Zhongyu Guo, Shuaiyu Liu, et al.
Autonomous navigation in unknown environments requires a robot to efficiently reach a predefined goal while exploring without prior maps. Although progress has been made in this area, most existing works still rely on traditional planning methods with hand-crafted rules, while le…