A Multimodal Perception System for Precise Landing of UAVs in Offshore Environments

IF 4.2 2区 计算机科学 Q2 ROBOTICS
Rafael Marques Claro, Francisco Soares Pinto Neves, Andry Maykol Gomes Pinto
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引用次数: 0

Abstract

The integration of precise landing capabilities into unmanned aerial vehicles (UAVs) is crucial for enabling autonomous operations, particularly in challenging environments such as the offshore scenarios. This work proposes a heterogeneous perception system that incorporates a multimodal fiducial marker, designed to improve the accuracy and robustness of autonomous landing of UAVs in both daytime and nighttime operations. This work presents ViTAL-TAPE, a visual transformer-based model, that enhance the detection reliability of the landing target and overcomes the changes in the illumination conditions and viewpoint positions, where traditional methods fail. VITAL-TAPE is an end-to-end model that combines multimodal perceptual information, including photometric and radiometric data, to detect landing targets defined by a fiducial marker with 6 degrees-of-freedom. Extensive experiments have proved the ability of VITAL-TAPE to detect fiducial markers with an error of 0.01 m. Moreover, experiments using the RAVEN UAV, designed to endure the challenging weather conditions of offshore scenarios, demonstrated that the autonomous landing technology proposed in this work achieved an accuracy up to 0.1 m. This research also presents the first successful autonomous operation of a UAV in a commercial offshore wind farm with floating foundations installed in the Atlantic Ocean. These experiments showcased the system's accuracy, resilience and robustness, resulting in a precise landing technology that extends mission capabilities of UAVs, enabling autonomous and Beyond Visual Line of Sight offshore operations.

海上环境下无人机精确着陆的多模态感知系统
将精确着陆能力集成到无人机(uav)中对于实现自主操作至关重要,特别是在海上等具有挑战性的环境中。这项工作提出了一个包含多模态基准标记的异构感知系统,旨在提高无人机在白天和夜间自主着陆的准确性和鲁棒性。本文提出了一种基于视觉变压器的ViTAL-TAPE模型,该模型提高了着陆目标的检测可靠性,克服了传统方法无法解决的光照条件和视点位置变化问题。VITAL-TAPE是一种端到端模型,结合了多模态感知信息,包括光度和辐射数据,以检测由6个自由度的基准标记定义的着陆目标。大量的实验证明了VITAL-TAPE检测基准标记物的能力,误差为0.01 m。此外,使用渡鸦无人机(RAVEN UAV)进行的实验表明,这项工作中提出的自主着陆技术实现了高达0.1米的精度。渡鸦无人机设计用于承受海上场景的恶劣天气条件。这项研究还展示了无人机在大西洋安装浮动基础的商业海上风电场中的首次成功自主操作。这些实验展示了系统的准确性、弹性和稳健性,从而实现了精确着陆技术,扩展了无人机的任务能力,实现了自主和超视距海上作业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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