Scholarlink

Continuous-Time Simultaneous Localization And Mapping (CTSLAM) has become a promising approach for fusing asynchronous and multi-modal sensor suites. Unlike discrete-time SLAM, which estimates poses discretely, CTSLAM uses continuous-time motion parametrizations, facilitating the integration of a variety of sensors such as rolling-shutter cameras, event cameras and Inertial Measurement Units (IMUs). However, CTSLAM approaches remain computationally demanding and are conventionally posed as centralized Non-Linear Least Squares (NLLS) optimizations. Targeting these limitations, we not only present the fastest SymForce-based [22] B- and Z-Spline implementations achieving speedups between 2.43x and 110.31x over Sommer et al. [40] but also implement a novel continuous-time Gaussian Belief Propagation (GBP) framework, coined Hyperion , which targets decentralized probabilistic inference across agents. We demonstrate the efficacy of our method in motion tracking and localization settings, complemented by empirical ablation studies. Code: https://github.com/VIS4ROB-lab/hyperion

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hyperion – A Fast, Versatile Symbolic Gaussian Belief Propagation Framework for Continuous-Time SLAM

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • David Hug,
  • Ignacio Alzugaray,
  • Margarita Chli

摘要

Continuous-Time Simultaneous Localization And Mapping (CTSLAM) has become a promising approach for fusing asynchronous and multi-modal sensor suites. Unlike discrete-time SLAM, which estimates poses discretely, CTSLAM uses continuous-time motion parametrizations, facilitating the integration of a variety of sensors such as rolling-shutter cameras, event cameras and Inertial Measurement Units (IMUs). However, CTSLAM approaches remain computationally demanding and are conventionally posed as centralized Non-Linear Least Squares (NLLS) optimizations. Targeting these limitations, we not only present the fastest SymForce-based [22] B- and Z-Spline implementations achieving speedups between 2.43x and 110.31x over Sommer et al. [40] but also implement a novel continuous-time Gaussian Belief Propagation (GBP) framework, coined Hyperion , which targets decentralized probabilistic inference across agents. We demonstrate the efficacy of our method in motion tracking and localization settings, complemented by empirical ablation studies. Code: https://github.com/VIS4ROB-lab/hyperion