collaborators

10 papers

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.RO2024

LHPF: Look back the History and Plan for the Future in Autonomous Driving

Sheng Wang, Yao Tian, Xiaodong Mei +5

Decision-making and planning in autonomous driving critically reflect the safety of the system, making effective planning imperative. Current imitation learning-based planning algo…

cs.RO2024

DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Driving

Sheng Wang, Ge Sun, Fulong Ma +5

Evaluating and training autonomous driving systems require diverse and scalable corner cases. However, most existing scene generation methods lack controllability, accuracy, and ve…