paper-with-me

홈 › Papers

FastBridge: Closing the Model-Based Realization Gap in Safety Filters on 3D Gaussian Splatting for Fast Quadrotor Flight

2026-07-01 · Tscholl Dario, Nakka Yashwanth Kumar, Gunter Brian arxiv

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.

📄 PDF Abstract BibTeX arXiv:2607.01200

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Digital filters with vanishing moments for shape analysis

2019-12-15 · Hugh L. Kennedy

Shape- and scale-selective digital-filters, with steerable finite/infinite impulse responses (FIR/IIRs) and non-recursive/recursive realizations, that are separable in both spatial dimensions and adequately isotropic, ar…

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics

2026-04-29 · Bernd Frauenknecht, Lukas Kesper, Daniel Mayfrank, Henrik Hose 외 arxiv

Predictive safety filters (PSFs) leverage model predictive control to enforce constraint satisfaction during deep reinforcement learning (RL) exploration, yet their reliance on first-principles models or Gaussian process…

Reinforcement LearningGaussian Processes

Quantifying uncertainties on excursion sets under a Gaussian random field prior

2015-01-15 · Dario Azzimonti, Julien Bect, Clément Chevalier, David Ginsbourger

We focus on the problem of estimating and quantifying uncertainties on the excursion set of a function under a limited evaluation budget. We adopt a Bayesian approach where the objective function is assumed to be a reali…

Improving the frequency response of Savitzky-Golay filters via colored-noise models

2019-12-18 · Hugh L Kennedy

Savitzky-Golay (SG) filters are finite impulse response (FIR) realizations of least-squares polynomial regression and they are widely used for filtering (e.g. smoothing, interpolating, predicting, differentiating) and pr…

Implicit Particle Filtering via a Bank of Nonlinear Kalman Filters

2022-05-09 · Iman Askari, Mulugeta A. Haile, Xuemin Tu, Huazhen Fang

The implicit particle filter seeks to mitigate particle degeneracy by identifying particles in the target distribution's high-probability regions. This study is motivated by the need to enhance computational tractability…