collaborators

8 papers

cs.CV2026

DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving

Feiyang jia, Lin Liu, Ziying Song +4

End-to-end (E2E) autonomous driving has recently attracted increasing interest in unifying Vision-Language-Action (VLA) with World Models to enhance decision-making and forward-loo…

cs.CV2026

SparseOccVLA: Bridging Occupancy and Vision-Language Models via Sparse Queries for Unified 4D Scene Understanding and Planning

Chenxu Dang, Jie Wang, Guang Li +6

In autonomous driving, Vision Language Models (VLMs) excel at high-level reasoning , whereas semantic occupancy provides fine-grained details. Despite significant progress in indiv…

cs.RO2026

The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms

Lingdong Kong, Shaoyuan Xie, Zeying Gong +135

Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under…

cs.RO2025

SocialNav-Map: Dynamic Mapping with Human Trajectory Prediction for Zero-Shot Social Navigation

Lingfeng Zhang, Erjia Xiao, Xiaoshuai Hao +7

Social navigation in densely populated dynamic environments poses a significant challenge for autonomous mobile robots, requiring advanced strategies for safe interaction. Existing…

cs.CV2025

Is your VLM Sky-Ready? A Comprehensive Spatial Intelligence Benchmark for UAV Navigation

Lingfeng Zhang, Yuchen Zhang, Hongsheng Li +7

Vision-Language Models (VLMs), leveraging their powerful visual perception and reasoning capabilities, have been widely applied in Unmanned Aerial Vehicle (UAV) tasks. However, the…

cs.RO2025

RoboAfford++: A Generative AI-Enhanced Dataset for Multimodal Affordance Learning in Robotic Manipulation and Navigation

Xiaoshuai Hao, Yingbo Tang, Lingfeng Zhang +6

Robotic manipulation and navigation are fundamental capabilities of embodied intelligence, enabling effective robot interactions with the physical world. Achieving these capabiliti…