让无人机在复杂环境中更快更稳飞行，解决传统安全过滤器不考虑电机限制的问题。
FastBridge: Closing the Model-Based Realization Gap in Safety Filters on 3D Gaussian Splatting for Fast Quadrotor Flight
- 基于3D高斯泼溅构建非线性安全过滤器，考虑实际电机响应能力。
- 轨迹抖动降低47%，计算速度提升2.25倍，实现实时飞行。
- 适合需要高速安全避障的无人机系统研发与工程部署。
快速四旋翼飞行需在有限机载算力下实现安全避障。尽管3D高斯泼溅（3DGS）提供了连续、几何感知的场景表征，用于感知驱动导航，但现有3DGS安全过滤器采用单/双积分器等简化模型，忽略执行器限制，并假设指令加速度可瞬时实现。本文基于3DGS的解析碰撞锥屏障，提出一种基于完整四旋翼动力学的非线性、执行器感知安全过滤器。推导出高相对阶的碰撞锥指数型控制屏障函数（CBF），并设计前向模拟备份策略，确保输入约束下的二次规划（QP）可行性。相较于最先进3DGS安全过滤器，本方法使轨迹抖动减少47%，运行速度提升2.25倍。我们在仿真和真实硬件上验证了该方法在感知生成的复杂环境中的实时导航性能。
原文摘要 · Abstract (English)
Fast quadrotor flight requires safe obstacle avoidance under tight onboard compute limits. While 3D Gaussian Splatting (3DGS) provides a continuous, geometry-aware scene representation for perception-driven navigation, existing 3DGS safety filters use reduced-order models such as single- and double-integrators that ignore actuator limits and assume commanded accelerations are realized instantaneously. Building on an analytic collision cone barrier for 3DGS, we introduce a nonlinear, actuator-aware safety filter enforced through the full quadrotor dynamics. We derive a high-relative-degree collision cone exponential CBF and a backup CBF that preserves QP feasibility under input constraints using a forward-simulated backup policy. Compared with a state-of-the-art 3DGS safety filter, our approach reduces trajectory jerk by 47% and runs 2.25 times faster. We validate the method in simulation and on hardware for real-time navigation in cluttered, perception-derived environments.
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