SUPER ODOMETRY 2.0：基于分层自适应的弹性里程计
SUPER ODOMETRY 2.0: Resilient Odometry via Hierarchical Adaptation
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中文总结 AI 辅助
本文提出Super Odometry 2.0传感器融合框架，通过分层自适应结构提升里程计鲁棒性，经多机器人多场景验证，为全退化环境下机器人自主提供支撑。
中文摘要 AI 辅助
弹性且鲁棒的里程计对于在复杂动态环境中运行的自主系统至关重要。现有里程计系统常受严重的传感器退化及烟雾、沙尘暴、雪或低光照等极端条件影响，威胁机器人的安全性与功能。为应对这些挑战，本文提出Super Odometry（一种传感器融合框架），可动态适应不同程度的环境退化。Super Odometry采用分层结构，整合了从低到高适应性的四个核心模块：自适应特征选择、自适应状态方向选择、自适应引擎选择，以及一种新型基于学习的惯性里程计。该惯性里程计在超过100小时的异构机器人平台数据上训练，可捕捉全面的运动动力学。Super Odometry将惯性测量单元（IMU）提升至与相机、激光雷达同等重要的地位，在外部传感器失效时提供可靠的后备支持。Super Odometry已在200公里里程、800运行小时的测试中，于空中、轮式、腿式机器人组成的机队上，在多样传感器配置、环境退化及剧烈运动场景下完成验证，为实现全退化环境下安全、长期的机器人自主迈出了重要一步。
英文摘要
Resilient and robust odometry is crucial for autonomous systems operating in complex and dynamic environments. Existing odometry systems often struggle with severe sensory degradations and extreme conditions such as smoke, sandstorms, snow, or low-light conditions, threatening both the safety and functionality of robots. To address these challenges, we present Super Odometry, a sensor fusion framework that dynamically adapts to varying levels of environmental degradation. Super Odometry employs a hierarchical structure to integrate four core modules from lower-level to higher-level adaptability including adaptive feature selection, adaptive state direction selection, adaptive engine selection, and a novel learning- based inertial odometry. The inertial odometry, trained on over 100 hours of heterogeneous robotic platforms, captures comprehensive motion dynamics. Super Odometry elevates the inertial measurement unit (IMU) to equal importance with camera and LiDAR within the sensor fusion framework, providing a reliable fallback when exteroceptive sensors fail. Super Odometry has been validated across 200 kilometers and 800 operational hours on a fleet of aerial, wheeled, and legged robots, under diverse sensor configurations, environmental degradation, and aggressive motion profiles. It marks an important step towards safe and long-term robotic autonomy in all-degraded environments.
发表机构
- Carnegie Mellon University（卡内基梅隆大学）
- University at Buffalo（布法罗大学）
机构由 AI 辅助整理，请以论文原文为准。
