4 papers
Libra-VLA: Achieving Learning Equilibrium via Asynchronous Coarse-to-Fine Dual-System
Yifei Wei, Linqing Zhong, Yi Liu +4
Vision-Language-Action (VLA) models are a promising paradigm for generalist robotic manipulation by grounding high-level semantic instructions into executable physical actions. How…
ACoT-VLA: Action Chain-of-Thought for Vision-Language-Action Models
Linqing Zhong, Yi Liu, Yifei Wei +4
Vision-Language-Action models have emerged as essential generalist robot policies for diverse manipulation tasks, conventionally relying on directly translating multimodal inputs i…
SkeNa: Learning to Navigate Unseen Environments Based on Abstract Hand-Drawn Maps
Haojun Xu, Jiaqi Xiang, Wu Wei +5
A typical human strategy for giving navigation guidance is to sketch route maps based on the environmental layout. Inspired by this, we introduce Sketch map-based visual Navigation…
TopV-Nav: Unlocking the Top-View Spatial Reasoning Potential of MLLM for Zero-shot Object Navigation
Linqing Zhong, Chen Gao, Zihan Ding +5
The Zero-Shot Object Navigation (ZSON) task requires embodied agents to find a previously unseen object by navigating in unfamiliar environments. Such a goal-oriented exploration h…