papers

Publications (13)

cs.CV2025

Talk2Event: Grounded Understanding of Dynamic Scenes from Event Cameras

Lingdong Kong, Dongyue Lu, Ao Liang +6

Event cameras offer microsecond-level latency and robustness to motion blur, making them ideal for understanding dynamic environments. Yet, connecting these asynchronous streams to…

cs.CV2025

Visual Grounding from Event Cameras

Lingdong Kong, Dongyue Lu, Ao Liang +6

Event cameras capture changes in brightness with microsecond precision and remain reliable under motion blur and challenging illumination, offering clear advantages for modeling hi…

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.RO2024

DHP-Mapping: A Dense Panoptic Mapping System with Hierarchical World Representation and Label Optimization Techniques

Tianshuai Hu, Jianhao Jiao, Yucheng Xu +3

Maps provide robots with crucial environmental knowledge, thereby enabling them to perform interactive tasks effectively. Easily accessing accurate abstract-to-detailed geometric a…

cs.RO2026

Stairway to Success: An Online Floor-Aware Zero-Shot Object-Goal Navigation Framework via LLM-Driven Coarse-to-Fine Exploration

Zeying Gong, Rong Li, Tianshuai Hu +6

Deployable service and delivery robots struggle to navigate multi-floor buildings to reach object goals, as existing systems fail due to single-floor assumptions and requirements f…

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…

cs.RO2026

NavThinker: Action-Conditioned World Models for Coupled Prediction and Planning in Social Navigation

Tianshuai Hu, Zeying Gong, Lingdong Kong +7

Social navigation requires robots to act safely in dynamic human environments. Effective behavior demands thinking ahead: reasoning about how the scene and pedestrians evolve under…

cs.CV2025

3EED: Ground Everything Everywhere in 3D

Rong Li, Yuhao Dong, Tianshuai Hu +7

Visual grounding in 3D is the key for embodied agents to localize language-referred objects in open-world environments. However, existing benchmarks are limited to indoor focus, si…

cs.RO2025

From Cognition to Precognition: A Future-Aware Framework for Social Navigation

Zeying Gong, Tianshuai Hu, Ronghe Qiu +1

To navigate safely and efficiently in crowded spaces, robots should not only perceive the current state of the environment but also anticipate future human movements. In this paper…

cs.RO2022

FusionPortable: A Multi-Sensor Campus-Scene Dataset for Evaluation of Localization and Mapping Accuracy on Diverse Platforms

Jianhao Jiao, Hexiang Wei, Tianshuai Hu +10

Combining multiple sensors enables a robot to maximize its perceptual awareness of environments and enhance its robustness to external disturbance, crucial to robotic navigation. T…

cs.RO2026

Token-Wise Latent Streaming from Slow Reasoners to Fast Planners for Dynamic Vision Language Navigation

Tianshuai Hu, Yangyi Zhong, Zeying Gong +7

Vision-Language Navigation in dynamic, human-centric environments exposes a fundamental tension: linguistic reasoning is slow and deliberative, whereas safe, socially compliant pla…

cs.RO2026

FLUX: Accelerating Cross-Embodiment Generative Navigation Policies via Rectified Flow and Static-to-Dynamic Learning

Zeying Gong, Yangyi Zhong, Yiyi Ding +6

Autonomous navigation requires a broad spectrum of skills, from static goal-reaching to dynamic social traversal, yet evaluation remains fragmented across disparate protocols. We i…

cs.RO2026

Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future

Tianshuai Hu, Xiaolu Liu, Song Wang +17

Autonomous driving has long relied on modular "Perception-Decision-Action" pipelines, where hand-crafted interfaces and rule-based components often break down in complex or long-ta…