الباحثون

Xuelong Li

المنشورات 11

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WAND: Learning Robust Navigation under Complex Wind Disturbances and Dense Obstacles for Quadrotors

Zhonghan Tang, Chenhui Li, Shuai Liang وآخرون · 2026 · 10.1109/lra.2026.3730214

Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which perturb vehicle dynamics, limit control authority, and substantially increase collision risk. Existing learning-based navigation policies typically rely on obstacle percept …

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Continuous Ground-Truth Construction and a Recovery Policy for Air--Water Robotic Tracking

Jiangong Xiao, Zhe Sun, Kanzhong Yao وآخرون · 2026

Visual tracking across the air-water interface is challenged by splashes, bubbles, refraction, reflections, and abrupt appearance changes that can temporarily invalidate observations. This setting poses two coupled difficulties: first, for evaluation, image-only annotation cannot reliably describe the target's physical …

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SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining

Jicong Ao, Shuhan Jiang, Yuling Zhong وآخرون · 2026

The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations for these interactions remains challenging due to the precise contact and constraint-following motions involved. Although simulation provides a promising alternative, exis …

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DistScene: Object-to-Scene Distillation for 3D Scene Generation

Kunming Luo, Hongyu Yan, Ken Deng وآخرون · 2026

We present DistScene, a framework for single-image compositional 3D scene generation by jointly modeling the environment and individual objects. Unlike existing methods that represent scenes primarily as collections of objects, we model the environment as an explicit scene component to provide geometric context for obj …

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MixVLA: Adaptive Mixing of Non-Invariant Information for Generalizable Vision-Language-Action Models

Pingrui Zhang, Yu Zhang, Pengyuan Wu وآخرون · 2026

Vision-Language-Action (VLA) models have achieved remarkable advances in robotic manipulation, yet their zero-shot generalization under out-of-distribution (OOD) conditions remains limited. These models often entangle task-relevant invariant structure with environment-specific non-invariant factors, causing policies to …

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Information Capacity of Generative Video Compression: Quantifying the Rate-Compute Exchange at Identical Quality

Under the AI Flow framework, communication networks distribute intelligence across devices, edge servers, and clouds, and computation at the receiver becomes a resource that can substitute for transmitted bits. Generative video compression (GVC) embodies this exchange by sending compact tokens with ultra-low bitrate an …

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AquaOrbit: Sim-to-Real Reinforcement Learning for Underwater Target Orbiting under Intermittent Visual Feedback

Kanzhong Yao, Jinyi Leng, Hao Zhang وآخرون · 2026

Intermittent visual loss disrupts target-relative feedback during underwater orbiting, making it difficult to maintain coordinated motion and reacquire a moving target. We present AquaOrbit, a reinforcement-learning controller with a recovery module for underwater target orbiting under interrupted visual feedback. Duri …

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Odometry-Aided Real-Time Mapping for Underwater Robots Using Forward-Looking Sonar

Siyuan Du, Kanzhong Yao, Youdong Wang وآخرون · 2026

Reliable perception is essential for underwater vehicles operating in complex environments, where light attenuation and scattering often degrade visibility and compromise optical sensing. Forward-looking sonar (FLS) offers an alternative by providing high-frame-rate acoustic imaging under poor optical conditions. Howev …

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Towards Reliable Underwater Diver-Robot Interaction: Gesture Design, Interaction Logic, and Real-World Evaluation

Yingqi Liu, Kanzhong Yao, Zimeng Peng وآخرون · 2026

Underwater human--robot interaction requires gesture commands that are both easy for divers to use and reliable for robots to recognize. We investigate these aspects through a closed-loop diver--robot interaction framework integrating a compact seven-gesture vocabulary, lightweight landmark-based recognition, and comma …

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