无人机的视觉SLAM:定位和感知
Licong Zhuang1, Xiaorong Zhong1, Linjie Xu2
1Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Yutang Street, Guangming District, Shenzhen 518132, China.
Sensors (Basel, Switzerland)
|May 25, 2024
概括
本次调查回顾了自主无人机 (UAV) 视觉同步定位和映射 (SLAM) 的情况. 它详细介绍了实时性能,无纹理和动态环境的进步,以改善无人机导航.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 计算机视觉 计算机视觉
- 自主系统 自主系统
背景情况:
- 定位和感知对于自主无人机 (UAV) 应用至关重要.
- 同时定位和映射 (SLAM) 是这些任务的关键技术,随着硬件,多传感器和人工智能的进步而发展.
研究的目的:
- 调查视觉SLAM的发展及其在无人机中的应用.
- 审查解决无人机视觉SLAM挑战的最先进的算法.
- 概述UAV本地化和感知方面的研究进展和未来方向.
主要方法:
- 审查最近和最先进的视觉SLAM算法.
- 对实时性能,无纹理和动态环境的解决方案的分析.
- 讨论无人机的视觉惯性融合和基于学习的增强.
主要成果:
- 确定了无人机视觉SLAM中的关键问题和解决方案.
- 强调了视觉惯性融合和基于学习的方法的作用.
- 提供了包括算法组件,摄像头配置和数据处理在内的全面初步资料.
结论:
- 视觉SLAM对于自主无人机至关重要,随着不断的进步.
- 未来的趋势指向增强实时性能,在具有挑战性的环境中的稳定性和AI集成.
- 该调查提供了对无人机视觉SLAM的十年长的视角,确定了研究缺口和未来的机会.
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