8 papers · 1 filter
Feeling the Unexpected: ResTacVLA for Contact-Rich Manipulation via Residual Tactile Representation
Pengwei Zhang, Bin Xie, Ce Hao +5
Tactile perception is indispensable for contact-rich manipulation, yet integrating it into Vision-Language-Action (VLA) models often induces modality collapse, where high-bandwidth…
MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models
Hao Shi, Weiye Li, Bin Xie +6
Temporal modeling is essential for robotic manipulation, as effective control requires both memory of past interactions and imagination of future states. However, most VLA models r…
PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
Xinyu Guo, Bin Xie, Wei Chai +4
Large-scale pretraining has made Vision-Language-Action (VLA) models promising foundations for generalist robot manipulation, yet adapting them to downstream tasks remains necessar…
GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning
Yufei Jia, Heng Zhang, Ziheng Zhang +39
Embodied AI research is undergoing a shift toward vision-centric perceptual paradigms. While massively parallel simulators have catalyzed breakthroughs in proprioception-based loco…
MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +7
Temporal context is essential for robotic manipulation because such tasks are inherently non-Markovian, yet mainstream VLA models typically overlook it and struggle with long-horiz…
SpatialActor: Exploring Disentangled Spatial Representations for Robust Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +5
Robotic manipulation requires precise spatial understanding to interact with objects in the real world. Point-based methods suffer from sparse sampling, leading to the loss of fine…