13 papers
A Topological Representation with Object-Path Graphs for Open-Vocabulary Instance Navigation
Linwei Zheng, Daojie Peng, Bingtao Wang +2
Vision-language navigation requires embodied agents to navigate environments using natural language instructions and visual observations. Existing approaches typically decompose na…
EmoPose: Vision-Language Model Guided Emotion-Aware Gesture Generation for Humanoid Robots
Daojie Peng, Bingtao Wang, Fulong Ma +3
Socially competent humanoid robots must communicate affect and intent through gesture as well as speech, yet open-ended interaction must become motion that is both expressive and e…
Latency-Tolerant Cloud-Edge Collaborative Vision-Language-Action Models via Emergent Representational Specialization
Daojie Peng, Fulong Ma, Bingtao Wang +2
Deploying billion-parameter Vision-Language-Action (VLA) policies on mobile robots creates a systems conflict: semantic reasoning benefits from cloud GPUs, whereas closed-loop cont…
SSTG-Nav: Metric-Grounded Spatial-Semantic Topological Graphs for Reusable Object Navigation
Daojie Peng, Bingtao Wang, Jun Ma
Service robots operating for months in the same homes, offices, and facilities should become more reliable with experience instead of searching familiar space from scratch for ever…
LeapBot-WA: World-Anchor Action Models via Predictive Latent Alignments
Pei Liu, Nan Zheng, Lang Zhang +8
World Action Models (WAMs) have emerged as a powerful paradigm for embodied intelligence, yet the prevailing reliance on pixel-level video generation creates a fundamental bottlene…
GeoSem-WAM: Geometry- and Semantic-Aware World Action Models
Fulong Ma, Daojie Peng, Wenjun Yue +4
Recent World Action Models (WAMs) have demonstrated impressive capabilities in embodied decision-making. However, whether their effectiveness stems from explicit future imagination…
AttenA+: Rectifying Action Inequality in Robotic Foundation Models
Daojie Peng, Fulong Ma, Jiahang Cao +7
Existing robotic foundation models, while powerful, are predicated on an implicit assumption of temporal homogeneity: treating all actions as equally informative during optimizatio…
IAF-Net: Illumination-Adaptive Fusion for Low-Light Urban Road Segmentation
Bingtao Wang, Daojie Peng, Fulong Ma +2
Semantic road segmentation is important for autonomous driving, but existing methods suffer severe performance degradation under low-light conditions. Many existing multi-modal fus…
LiteViLNet: Lightweight Vision-LiDAR Fusion Network for Efficient Road Segmentation
Daojie Peng, Bingtao Wang, Fulong Ma +2
Road segmentation is a fundamental perception task for autonomous driving and mobile robotics, where both appearance and geometric cues must be processed under edge-computing const…
Annotation-Free Detection of Drivable Areas and Curbs Leveraging LiDAR Point Cloud Maps
Fulong Ma, Daojie Peng, Jun Ma
Drivable areas and curbs are critical traffic elements for autonomous driving, forming essential components of the vehicle visual perception system and ensuring driving safety. Dee…
Structured Observation Language for Efficient and Generalizable Vision-Language Navigation
Daojie Peng, Fulong Ma, Jun Ma
Vision-Language Navigation (VLN) requires an embodied agent to navigate complex environments by following natural language instructions, which typically demands tight fusion of vis…
TopoNav: Topological Graphs as a Key Enabler for Advanced Object Navigation
Peiran Liu, Qiang Zhang, Daojie Peng +6
Object Navigation (ObjectNav) has made great progress with large language models (LLMs), but still faces challenges in memory management, especially in long-horizon tasks and dynam…
LOVON: Legged Open-Vocabulary Object Navigator
Daojie Peng, Jiahang Cao, Qiang Zhang +1
Object navigation in open-world environments remains a formidable and pervasive challenge for robotic systems, particularly when it comes to executing long-horizon tasks that requi…