GRVINS:紧密耦合的全球导航卫星系统--测距--视觉--惯性系统

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent & Robotic Systems Pub Date : 2024-02-22 DOI:10.1007/s10846-023-02033-8
Bing-Xian Lu, Yu-Chung Tsai, Kuo-Shih Tseng
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引用次数: 0

摘要

桥梁检测目前是一项劳动密集型任务。利用无人飞行器(UAV)协助检测任务是一个很有前景的方向。然而,让无人飞行器进行自主检测涉及到无人飞行器状态估计问题。由于无人飞行器的部分传感器可能不可用,因此如何通过传感器融合来估计状态是关键。本文提出了一种基于紧耦合非线性优化的系统,该系统集成了四种传感器:摄像头、IMU、超宽带(UWB)测距和全球导航卫星系统(GNSS)。由于采用了紧密耦合的多传感器融合方法和系统设计,该系统充分利用了四种传感器的优势,能够无缝响应室内外 GNSS 和 UWB 的丢失或重新获取。它能有效减少长期轨迹漂移,并提供平滑、连续的状态估计。实验结果表明,所提出的方法优于最先进的方法。
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GRVINS: Tightly Coupled GNSS-Range-Visual-Inertial System

Bridge inspection is currently a labor intensive task. Utilizing unmanned aerial vehicles (UAVs) to assist in inspection tasks is a promising direction. However, enabling UAVs for autonomous inspection involves the UAV state estimation problems. Since parts of UAV sensors could be unavailable, how to estimate states via sensor fusion is the key. In this paper, we propose a tightly-coupled nonlinear optimization-based system that integrates four kinds of sensors: camera, IMU, Ultra-wideband (UWB) range measurements, and global navigation satellite system (GNSS). Due to the tightly-coupled multi-sensor fusion method and system design, the system takes the advantage of the four sensors, and can seamlessly respond to indoor and outdoor GNSS and UWB loss or reacquisition. It can effectively reduce the long-term trajectory drift and provide smooth and continuous state estimation. The experimental results show that the proposed method outperforms the state-of-the-art approaches.

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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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