7 papers · 1 filter
Sensing Which Modality Matters: Evidence-Gated Regularization for Robust VLA Policies
Yue Yang, Diego Romeres, Chiori Hori +3
Vision-Language-Action (VLA) policies fuse multimodal sensory inputs, but training on limited and homogeneous robot demonstrations encourages spurious inter-sensor correlations rat…
DenseReward: Dense Reward Learning via Failure Synthesis for Robotic Manipulation
Yu Fang, Wanxi Dong, Jiaqi Liu +7
Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning. However, its practical adoption remains bottlenecked by the lack of…
Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation
Chenyang Ma, Yunchao Yao, Zhenyu Wei +3
Compliance is essential for dexterous manipulation, yet existing solutions often rely on external tactile or force sensors that are costly, fragile, and difficult to deploy on low-…
Robotic VLA Benefits from Joint Learning with Motion Image Diffusion
Yu Fang, Kanchana Ranasinghe, Le Xue +10
Vision-Language-Action (VLA) models have achieved remarkable progress in robotic manipulation by mapping multimodal observations and instructions directly to actions. However, they…
BOSS: Benchmark for Observation Space Shift in Long-Horizon Task
Yue Yang, Linfeng Zhao, Mingyu Ding +2
Robotics has long sought to develop visual-servoing robots capable of completing previously unseen long-horizon tasks. Hierarchical approaches offer a pathway for achieving this go…
ARCADE: Scalable Demonstration Collection and Generation via Augmented Reality for Imitation Learning
Yue Yang, Bryce Ikeda, Gedas Bertasius +1
Robot Imitation Learning (IL) is a crucial technique in robot learning, where agents learn by mimicking human demonstrations. However, IL encounters scalability challenges stemming…