用逼真视觉模拟训练无人机自主飞行，安全高效。
VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots
- 通过3D高斯泼溅生成实时真实感视觉数据
- 系统更新率达100Hz，支持无风险算法测试
- 配套开源课程与硬件指南，适合教学使用
自主飞行机器人正日益融入日常生活。实践型空中机器人课程对培养下一代人才至关重要。此类高效且吸引人的课程依赖于可靠的实验平台。本文提出VizFlyt，一个开源的以感知为中心的硬件在环（HITL）逼真视觉测试框架，用于空中机器人教学。我们利用外部定位系统提供的位姿信息，通过3D高斯泼溅技术实时生成逼真的视觉传感器数据，使无人机自主算法可在无碰撞风险的情况下进行测试。系统实现超过100Hz的更新率。基于过往教学经验，我们进一步构建了基于VizFlyt的开源、开放硬件课程体系。我们在真实世界中进行了多类课程项目验证，结果表明该系统有效且具备广泛的应用潜力。代码、数据集、硬件指南及演示视频已公开于 https://pear.wpi.edu/research/vizflyt.html。
原文摘要 · Abstract (English)
Autonomous aerial robots are becoming commonplace in our lives. Hands-on aerial robotics courses are pivotal in training the next-generation workforce to meet the growing market demands. Such an efficient and compelling course depends on a reliable testbed. In this paper, we present VizFlyt, an open-source perception-centric Hardware-In-The-Loop (HITL) photorealistic testing framework for aerial robotics courses. We utilize pose from an external localization system to hallucinate real-time and photorealistic visual sensors using 3D Gaussian Splatting. This enables stress-free testing of autonomy algorithms on aerial robots without the risk of crashing into obstacles. We achieve over 100Hz of system update rate. Lastly, we build upon our past experiences of offering hands-on aerial robotics courses and propose a new open-source and open-hardware curriculum based on VizFlyt for the future. We test our framework on various course projects in real-world HITL experiments and present the results showing the efficacy of such a system and its large potential use cases. Code, datasets, hardware guides and demo videos are available at https://pear.wpi.edu/research/vizflyt.html
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