6 papers
RIFAR: Reliability-Informed and Forgetting-Aware Replay for Continual Robot Learning with World-Action Models
Zirui Song, Tu Lin, Zirong Song +11
Genuine embodied agency requires robots to turn continuous real-world experience into lasting, transferable skills. This demands continual learning that integrates new capabilities…
LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies
Zheng Lu, Zirong Song, Haoran Liao +11
Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hierarchical visual-semantic repr…
DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration
Haoran Liao, Pengyue Wang, Shuoyu Chen +10
Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that are moving or require rapid adj…
LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion
Jiangran Lyu, Kai Liu, Xuheng Zhang +20
Recent robot foundation models largely rely on large-scale behavior cloning, which imitates expert actions but discards transferable dynamics knowledge embedded in heterogeneous em…
CycleManip: Enabling Cyclic Task Manipulation via Effective Historical Perception and Understanding
Yi-Lin Wei, Haoran Liao, Yuhao Lin +4
In this paper, we explore an important yet underexplored task in robot manipulation: cycle-based manipulation, where robots need to perform cyclic or repetitive actions with an exp…
TypeTele: Releasing Dexterity in Teleoperation by Dexterous Manipulation Types
Yuhao Lin, Yi-Lin Wei, Haoran Liao +6
Dexterous teleoperation plays a crucial role in robotic manipulation for real-world data collection and remote robot control. Previous dexterous teleoperation mostly relies on hand…