5 papers
Spatial-Temporal Aware Visuomotor Diffusion Policy Learning
Zhenyang Liu, Yikai Wang, Kuanning Wang +3
Visual imitation learning is effective for robots to learn versatile tasks. However, many existing methods rely on behavior cloning with supervised historical trajectories, limitin…
A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding
Zhenyang Liu, Sixiao Zheng, Siyu Chen +4
Open-vocabulary 3D visual grounding aims to localize target objects based on free-form language queries, which is crucial for embodied AI applications such as autonomous navigation…
RAG-6DPose: Retrieval-Augmented 6D Pose Estimation via Leveraging CAD as Knowledge Base
Kuanning Wang, Yuqian Fu, Tianyu Wang +4
Accurate 6D pose estimation is key for robotic manipulation, enabling precise object localization for tasks like grasping. We present RAG-6DPose, a retrieval-augmented approach tha…
ReasonGrounder: LVLM-Guided Hierarchical Feature Splatting for Open-Vocabulary 3D Visual Grounding and Reasoning
Zhenyang Liu, Yikai Wang, Sixiao Zheng +4
Open-vocabulary 3D visual grounding and reasoning aim to localize objects in a scene based on implicit language descriptions, even when they are occluded. This ability is crucial f…
Topo-Field: Topometric mapping with Brain-inspired Hierarchical Layout-Object-Position Fields
Jiawei Hou, Wenhao Guan, Longfei Liang +3
Mobile robots require comprehensive scene understanding to operate effectively in diverse environments, enriched with contextual information such as layouts, objects, and their rel…