Valme Daniil, Rassõlkin Anton, Liyanage Dhanushka C
Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia.
Kuressaare College, Tallinn University of Technology, 93811 Kuressaare, Estonia.
Sensors (Basel). 2025 Apr 8;25(8):2346. doi: 10.3390/s25082346.
Hyperspectral imaging (HSI) has evolved from its origins in space missions to become a promising sensing technology for mobile ground robots, offering unique capabilities in material identification and scene understanding. This review examines the integration and applications of HSI systems in ground-based mobile platforms, with emphasis on outdoor implementations. The analysis covers recent developments in two main application domains: autonomous navigation and inspection tasks. In navigation, the review explores HSI applications in Advanced Driver Assistance Systems (ADAS) and off-road scenarios, examining how spectral information enhances environmental perception and decision making. For inspection applications, the investigation covers HSI deployment in search and rescue operations, mining exploration, and infrastructure monitoring. The review addresses key technical aspects including sensor types, acquisition modes, and platform integration challenges, particularly focusing on environmental factors affecting outdoor HSI deployment. Additionally, it analyzes available datasets and annotation approaches, highlighting their significance for developing robust classification algorithms. While recent advances in sensor design and processing capabilities have expanded HSI applications, challenges remain in real-time processing, environmental robustness, and system cost. The review concludes with a discussion of future research directions and opportunities for advancing HSI technology in mobile robotics applications.
高光谱成像(HSI)已从其在太空任务中的起源发展成为一种适用于移动地面机器人的有前景的传感技术,在材料识别和场景理解方面具有独特能力。本综述研究了HSI系统在地面移动平台中的集成与应用,重点关注户外应用。分析涵盖了两个主要应用领域的最新进展:自主导航和检测任务。在导航方面,综述探讨了HSI在高级驾驶辅助系统(ADAS)和越野场景中的应用,研究光谱信息如何增强环境感知和决策制定。对于检测应用,研究涵盖了HSI在搜索救援行动、采矿勘探和基础设施监测中的部署。综述讨论了关键技术方面,包括传感器类型、采集模式和平台集成挑战,特别关注影响户外HSI部署的环境因素。此外,还分析了可用数据集和标注方法,强调了它们对开发强大分类算法的重要性。虽然传感器设计和处理能力的最新进展扩大了HSI的应用,但在实时处理、环境鲁棒性和系统成本方面仍存在挑战。综述最后讨论了未来的研究方向以及在移动机器人应用中推进HSI技术的机会。