首页|面向未知环境的自主无人机智能感知测量技术

面向未知环境的自主无人机智能感知测量技术

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智能化测绘的发展对数据采集高效性、完备性和智能性提出了更高的要求.尤其是在林下等GNSS拒止环境下,现有传统手段往往难以完成高效率、高覆盖率测量.为了满足未知环境的智能化感知测量需求,以无人机为移动平台,本文设计并提出了一种融合视觉在线自主定位及全局探测路径规划的自主无人机智能感知测量技术与总体框架.本文首先设计并采用了 一种基于点线特征的VIO(visual-inertial odometry)在线定位算法,通过点线特征的提取和匹配进行初始位姿的解算,之后利用因子图优化实时地输出无人机高精度的位姿信息.进一步地,为了实现无人机对于未知环境高效且高覆盖率的自主测量,采用了一种顾及多层次信息的全局最优探测路径规划方法确定局部最佳探测目标,然后通过轨迹搜索和优化算法实时地生成高质量的探测运动轨迹.通过自主搭建无人机平台对该技术框架进行了验证,分步对比和总体真实试验表明框架设计并采用的定位及空间探测方法相较于目前具有代表性的方法具有明显优势,并且在GNSS拒止局部林下环境中实现了高效高覆盖率的全自主测量,为未知场景进一步的在线智能化感知奠定了良好的理论方法与框架基础.
Intelligent perception measurement technology of autonomous UAV for unknown environment
The development of intelligent surveying and mapping puts higher requirements for efficient,complete,and intelli-gent data collection,especially in GNSS-denied environments such as under-canopy,where traditional methods frequently struggle to achieve efficient and high-coverage measurements.To address the need for intelligent perception measurement of unknown environments,this paper introduces a novel intelligent perception measurement unmanned aerial vehicle(UAV)tech-nology and framework,using a UAV as a mobile platform.This paper integrates visual online autonomous localization with global exploration path planning.Initially,the framework incorporates a novel visual-inertial odometry(VIO)online localiza-tion algorithm based on point and line features,which solves the initial pose estimation through feature extraction and matching of point and line features,and then high-precision pose information of the UAV is generated in real-time using factor graph op-timization.Furthermore,to ensure efficient and high-coverage autonomous UAV measurements in unknown environments,this paper employs a global optimal exploration path planning method that considers multi-level information to determine the local exploration targets,and then generates high-quality exploration trajectories in real time through trajectory search and opti-mization algorithm.Moreover,the framework was validated by a customized UAV platform,the step-by-step comparison and overall real-world test demonstrates that the localization and space exploration methods designed and adopted by the framework have significant advantages compared with the current representative methods.In addition,it achieves efficient and high-cover-age full autonomous measurements in GNSS-denied local under-canopy environments,which establishes a solid theoretical and framework foundation for the further development of online intelligent perception in unknown scenarios.

autonomous UAVintelligent perception measurements technology and frameworkonline visual localizationau-tonomous planning and space exploration

闫利、赵英豪、戴集成、徐博、谢洪、周玉泉

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武汉大学测绘学院,湖北武汉 430079

湖北珞珈实验室,湖北武汉 430079

信息工程大学地理空间信息学院,河南郑州 450001

自主无人机 智能感知测量技术与框架 在线视觉定位 自主规划与空间探测

国家自然科学基金国家自然科学基金湖北省重大科技项目湖北珞珈实验室开放基金

42394061423714512021AAA010220100053

2024

10.11947/j.AGCS.2024.20230389

测绘学报
中国测绘学会

测绘学报

CSTPCD北大核心
影响因子：1.602
ISSN：1001-1595
年,卷(期)：2024.53(6)
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