7 papers · 1 filter
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…
RMBench: Memory-Dependent Robotic Manipulation Benchmark with Insights into Policy Design
Tianxing Chen, Yuran Wang, Mingleyang Li +16
Robotic manipulation policies have made rapid progress in recent years, yet most existing approaches give limited consideration to memory capabilities. Consequently, they struggle…
Minimalist Compliance Control
Haochen Shi, Songbo Hu, Yifan Hou +3
Compliance control is essential for safe physical interaction, yet its adoption is limited by hardware requirements such as force torque sensors. While recent reinforcement learnin…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation
Chen Wang, Haochen Shi, Weizhuo Wang +3
Imitation learning from human hand motion data presents a promising avenue for imbuing robots with human-like dexterity in real-world manipulation tasks. Despite this potential, su…