6 papers · 1 filter
Ego2Contact: Predicting Touch from Egocentric Human Video for Contact-Rich Robot Manipulation
Qianqian Yang, Dayou Li, Bangya Liu +11
Contact locations and interaction forces are critical for contact-rich robot manipulation but are often ambiguous from vision alone. Measuring them on robots requires specialized t…
Disentangling Task-Relevant Latent Dynamics for Reward Modeling
Dayou Li, Jionghao Wang, Peihao Wang +9
Reward design remains a major bottleneck for reinforcement learning in robotic manipulation. Handcrafted dense rewards can compensate for the limited guidance provided by sparse re…
RoboIRS: Inference-Time Internal Representation Steering for Generalist Robot Policies
Jiuzhou Lei, Chang Liu, Dayou Li +5
Vision-language-action (VLA) and world-action models (WAMs) often degrade under out-of-distribution task variations despite retaining partial task capability. To recover such capab…
PHR-VLA: Planning Horizon Reasoning for Vision-Language-Action Models
Davood Soleymanzadeh, Kaidi Zhang, Zhiyuan Zhang +4
Vision-language-action models (VLAs) have shown strong promise for general-purpose robotic manipulation by mapping language instructions and vision observations directly to actions…
Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations
Zhiyuan Zhang, Adeesh Desai, Jyun-Chi Hu +7
Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenanc…
ContactWorld: What Representations Matter for Vision-Tactile Latent World Models in Contact-Rich Manipulation
Zhiyuan Zhang, Pokuang Zhou, Kaidi Zhang +7
Contact-rich manipulation poses a fundamental challenge for world models: visual and tactile observations capture different aspects of physical interaction, and their utility depen…