6 papers · 1 filter
APEX: Adaptive Policy Execution for Precise Manipulation
Mengfei Zhao, Chenxi Jiang, Tuo An +2
Modern imitation learning methods, including visuomotor and Vision-Language-Action (VLA) policies, typically output high-level action references that are executed by low-level cont…
MARS Policy: Multimodality Only When It Matters
Jindou Jia, Tuo An, Yuxuan Hu +7
Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to capture diverse yet valid behavior…
Feedback World Model Enables Precise Guidance of Diffusion Policy
Tuo An, Jindou Jia, Gen Li +8
World models aim to improve robotic decision making by predicting the consequences of actions. However, in practice, their predictions often become unreliable once the robot encoun…
FLASH: Efficient Visuomotor Policy via Sparse Sampling
Jiaqi Bai, Jindou Jia, Yuxuan Hu +5
Generative models such as diffusion and flow matching have become dominant paradigms for visuomotor policy learning, yet their reliance on iterative denoising incurs high inference…
World Model for Robot Learning: A Comprehensive Survey
Bohan Hou, Gen Li, Jindou Jia +15
World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They support policy learning, planni…
Action-to-Action Flow Matching
Jindou Jia, Gen Li, Xiangyu Chen +5
Diffusion-based policies have recently achieved remarkable success in robotics by formulating action prediction as a conditional denoising process. However, the standard practice o…