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cs.RO2026
Behavior-Aligned Action Tokenization for Robot Policy Learning
Junbo Dong, Ze Chen, Zhendong Xie +5
Autoregressive robot policies learn continuous control by predicting discrete action tokens from observations. Different tasks often share local motions, yet behavioral corresponde…
cs.RO2026
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
Yuran Wang, Siqiao Huang, Mingleyang Li +21
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are…
cs.RO2026
Smoother Action Chunking Flow Policy via Prior-Corrected Orthogonal Trust-Region Guidance
Kai Fang, Hailong Pei, Xuemin Chi
Flow-matching robot policies commonly use action-chunking inference for efficient closed-loop control, but chunk boundaries can introduce discontinuous action transitions. Existing…