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Preprint Sep 2026

An Open Panoramic Aerial Robot: Airframe-Integrated Multi-Fisheye Sensing, Onboard ERP Formation, and Field Evaluation

We present an open panoramic aerial robot with four synchronized fisheye cameras integrated into a carbon-fiber airframe and an onboard NVIDIA Jetson Orin NX. The robot outputs calibrated raw views and an equirectangular panorama (ERP; 1280x640 in all experiments). The ERP pipeline uses overlap-specific projection radi...

Dun Dai, Zeping Lu, Cheng He et al. · 0 citations
Review Sep 2026

Towards Aerial Embodied Intelligence: Current Status and Challenges

Unmanned Aerial Vehicle (UAV) technology is undergoing a paradigm shift from sensing platforms to Aerial Embodied Intelligence (AEI) systems capable of physical manipulation. This paper provides a structured review of this emerging field, clarifying its definition, core tasks, and current technological bottlenecks. Spe...

Quan Quan, Jin-Hui Wang · 0 citations
Preprint Sep 2026

Time-Efficient Iterative Learning Planning for Safety-Critical Dynamic Obstacle Avoidance

Autonomous mobile robots require timeefficient planning and safety-critical dynamic obstacle avoidance under constrained onboard computation. While Iterative Learning Planning (ILP) offers lightweight and efficient traversal planning, it lacks explicit mechanisms for dynamic obstacle perception and avoidance. This arti...

Zhi-Yi Chen, Shu-Li Lv, Chen Min et al. · 0 citations
Preprint Sep 2026

From Multi-Fisheye Sensing to Panoramic Perception: A Parallax-Aware Onboard Platform for Ultra-Low-Altitude UAVs

Ultra-low-altitude unmanned aerial vehicles (UAVs) require surround vision near buildings, vegetation, and other obstacles. We present a parallax-aware onboard platform that converts four synchronized fisheye streams into an open 1280x640 equirectangular panorama (ERP) interface. A purpose-built carbon-fiber airframe i...

Dun Dai, Zeping Lu, Cheng He et al. · 0 citations
Review Aug 2026

VIP: Variation-based Iterative-learning Planning for Robotic Navigation

Extensive simulations and real-world experiments demonstrate that the proposed framework can efficiently generate and iteratively improve motion plans for different planning objectives, robotic platforms, and swarm configurations, highlighting its effectiveness, computational efficiency, and scalability as a general pl...

Shu-Li Lv, Pengda Mao, Chen Min et al. · 0 citations

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