6 papers
P3: Probabilistic Policy Propagation for Stable VAE-Based Robot Learning
Liyun Yan, Jianming Ma, Yang Zhang +5
Variational Autoencoders are widely used to encode high-dimensional and noisy observations in robotics. However, their stochastic latent creates a mismatch with Proximal Policy Opt…
Global-Local Attention Decomposition for Terrain Encoding in Humanoid Perceptive Locomotion
Shengcheng Fu, Yang Zhang, Zhanxiang Cao +4
Although reinforcement learning has significantly advanced humanoid locomotion, perceptive policies still struggle on sparse-foothold terrain and constrained environments. Success…
GeoAlign: Beyond Semantics with State-Guided Spatial Alignment in VLA Models
Yizhi Chen, Zhanxiang Cao, Xinyi Peng +14
Current Vision--Language--Action (VLA) models often optimize for semantic grounding, whereas executable manipulation requires geometry-aware spatial alignment and dynamic affordanc…
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms
Yufei Jia, Zhanxiang Cao, Mingrui Yu +48
Simulation-based RL for contemporary robot control is increasingly organized around GPU-resident simulation: physics, rollout collection, and learning are placed on a single GPU-ce…
HierKick: Hierarchical Reinforcement Learning for Vision-Guided Soccer Robot Control
Yizhi Chen, Zheng Zhang, Zhanxiang Cao +7
Controlling soccer robots involves multi-time-scale decision-making, which requires balancing long-term tactical planning and short-term motion execution. Traditional end-to-end re…
HiWET: Hierarchical World-Frame End-Effector Tracking for Long-Horizon Humanoid Loco-Manipulation
Zhanxiang Cao, Liyun Yan, Yang Zhang +7
Humanoid loco-manipulation requires executing precise manipulation tasks while maintaining dynamic stability amid base motion and impacts. Existing approaches typically formulate c…