1 citations · 1 across the 10 of their papers we have counts for
11 papers
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…
Comparative Evaluation of 3D Reconstruction Methods for Immersive Visualization of Laboratory Objects
Brian De La Cruz, Aaron Y. Zhao, Maitrey Gramopadhye +4
In this study, we examined whether current 3D reconstruction methods can support the creation of realistic holographic representations of laboratory objects for educational use. In…
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-…
When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs
Yu Fang, Yuchun Feng, Dong Jing +5
Vision-Language-Action models (VLAs) promise to ground language instructions in robot control, yet in practice often fail to faithfully follow language. When presented with instruc…
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…
ReBot: Scaling Robot Learning with Real-to-Sim-to-Real Robotic Video Synthesis
Yu Fang, Yue Yang, Xinghao Zhu +4
Vision-language-action (VLA) models present a promising paradigm by training policies directly on real robot datasets like Open X-Embodiment. However, the high cost of real-world d…
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…
Augmented Reality Demonstrations for Scalable Robot Imitation Learning
Yue Yang, Bryce Ikeda, Gedas Bertasius +1
Robot Imitation Learning (IL) is a widely used method for training robots to perform manipulation tasks that involve mimicking human demonstrations to acquire skills. However, its…
Paper index: Designing an introductory HRI course (workshop at HRI 2024)
Henny Admoni, Daniel Szafir, Wafa Johal +1
Human-robot interaction is now an established discipline. Dozens of HRI courses exist at universities worldwide, and some institutions even offer degrees in HRI. However, although…