FastBridge: Closing the Model-Based Realization Gap in Safety Filters on 3D Gaussian Splatting for Fast Quadrotor Flight
2026-07-01 • Robotics
Robotics
AI summaryⓘ
The authors improve how tiny flying robots called quadrotors avoid obstacles while flying fast. They use a method called 3D Gaussian Splatting to understand the environment but add a new safety check that considers the robot's real movement limits, not just simple models. This new approach makes the flight smoother and the calculations faster. They tested it both in computer simulations and with real robots in busy surroundings to show it works well.
quadrotor3D Gaussian Splattingcollision conecontrol barrier functionactuator constraintstrajectory jerkreal-time navigationperception-driven navigation
Authors
Tscholl Dario, Nakka Yashwanth Kumar, Gunter Brian
Abstract
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.