带超宽立体相机的微型飞行器的高效地形跟踪

M. Müller, S. Stoneman, Ingo von Bargen, Florian Steidle, W. Stürzl
{"title":"带超宽立体相机的微型飞行器的高效地形跟踪","authors":"M. Müller, S. Stoneman, Ingo von Bargen, Florian Steidle, W. Stürzl","doi":"10.1109/AERO47225.2020.9172781","DOIUrl":null,"url":null,"abstract":"In recent years, Micro Aerial Vehicles (MAVs) have drawn attention to the aerospace community. With such autonomous flying platforms, it is possible to explore foreign extraterrestrial bodies in an efficient and faster manner than other robotic platforms, like rovers. In addition, they can be equipped with a variety of different sensors. Cameras are especially well suited, since they are light, energy-efficient and deliver a broad spectrum of information. Following the underlying terrain in a defined height is a fundamental task for any exploring MAV. To accomplish this, many systems possess a designated height sensor, which in most cases only delivers a single height estimation taken from nadir. In such a setup, the MAV is just adjusting its height based on the current height estimation and does not take any terrain lying ahead into account, which results in delayed height adjustments. In this paper, we propose a novel method based on a wide-angle stereo camera setup, which is attached to the MAV, to overcome such problems. Due to the wide vertical field of view, the vehicle is able to not only measure its current height, but also the terrain lying ahead. Therefore, the MAV is able to perform a better terrain following compared to other methods, which use just a single nadir height sample. Our algorithm only needs to take the depth image, calculated by the stereo cameras, and the estimated gravity vector into account. Therefore, our method is very fast and computationally efficient, compared to other methods, which build up an entire map beforehand. As a result, the procedure presented here is also suitable for tiny flying systems with low computational capabilities and memory resources. The terrain following algorithm runs in real-time and on board the system, and is therefore also suitable for confined environments, like caves, and where communication delays are present. We evaluate our method with simulated data and real tests on an MAV. To demonstrate that our method works in a variety of different terrains, we show experiments with different slopes and obstacles in the flight path. We also compare our method to a basic terrain following by using just a single height measurement in a more classical approach.","PeriodicalId":114560,"journal":{"name":"2020 IEEE Aerospace Conference","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Efficient Terrain Following for a Micro Aerial Vehicle with Ultra-Wide Stereo Cameras\",\"authors\":\"M. Müller, S. Stoneman, Ingo von Bargen, Florian Steidle, W. Stürzl\",\"doi\":\"10.1109/AERO47225.2020.9172781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, Micro Aerial Vehicles (MAVs) have drawn attention to the aerospace community. With such autonomous flying platforms, it is possible to explore foreign extraterrestrial bodies in an efficient and faster manner than other robotic platforms, like rovers. In addition, they can be equipped with a variety of different sensors. Cameras are especially well suited, since they are light, energy-efficient and deliver a broad spectrum of information. Following the underlying terrain in a defined height is a fundamental task for any exploring MAV. To accomplish this, many systems possess a designated height sensor, which in most cases only delivers a single height estimation taken from nadir. In such a setup, the MAV is just adjusting its height based on the current height estimation and does not take any terrain lying ahead into account, which results in delayed height adjustments. In this paper, we propose a novel method based on a wide-angle stereo camera setup, which is attached to the MAV, to overcome such problems. Due to the wide vertical field of view, the vehicle is able to not only measure its current height, but also the terrain lying ahead. Therefore, the MAV is able to perform a better terrain following compared to other methods, which use just a single nadir height sample. Our algorithm only needs to take the depth image, calculated by the stereo cameras, and the estimated gravity vector into account. Therefore, our method is very fast and computationally efficient, compared to other methods, which build up an entire map beforehand. As a result, the procedure presented here is also suitable for tiny flying systems with low computational capabilities and memory resources. The terrain following algorithm runs in real-time and on board the system, and is therefore also suitable for confined environments, like caves, and where communication delays are present. We evaluate our method with simulated data and real tests on an MAV. To demonstrate that our method works in a variety of different terrains, we show experiments with different slopes and obstacles in the flight path. We also compare our method to a basic terrain following by using just a single height measurement in a more classical approach.\",\"PeriodicalId\":114560,\"journal\":{\"name\":\"2020 IEEE Aerospace Conference\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Aerospace Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AERO47225.2020.9172781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Aerospace Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AERO47225.2020.9172781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

近年来,微型飞行器(MAVs)引起了航空航天界的广泛关注。有了这样的自主飞行平台,就有可能以比其他机器人平台(如漫游者)更有效、更快的方式探索外星天体。此外,它们还可以配备各种不同的传感器。相机尤其适合,因为它们轻便、节能,并能传递广泛的信息。在确定的高度跟踪底层地形是任何探索MAV的基本任务。为了做到这一点,许多系统都有一个指定的高度传感器,在大多数情况下,它只提供从最低点提取的单一高度估计。在这种设置中,MAV只是根据当前的高度估计来调整其高度,而不会考虑前方的任何地形,这导致高度调整延迟。在本文中,我们提出了一种基于广角立体摄像机的新方法,该方法附加在MAV上,以克服这些问题。由于宽阔的垂直视野,车辆不仅可以测量当前高度,还可以测量前方的地形。因此,与其他仅使用单一最低点高度样本的方法相比,MAV能够执行更好的地形跟踪。我们的算法只需要考虑由立体摄像机计算的深度图像和估计的重力矢量。因此,与其他预先建立整个地图的方法相比,我们的方法非常快速且计算效率高。因此,本文提出的程序也适用于计算能力和内存资源较低的微型飞行系统。地形跟踪算法在系统上实时运行,因此也适用于狭窄的环境,如洞穴,以及存在通信延迟的地方。我们用仿真数据和MAV的实际测试来评估我们的方法。为了证明我们的方法适用于各种不同的地形,我们展示了飞行路径中不同坡度和障碍物的实验。我们还将我们的方法与基本地形进行比较,然后使用更经典的方法中仅使用单个高度测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Efficient Terrain Following for a Micro Aerial Vehicle with Ultra-Wide Stereo Cameras
In recent years, Micro Aerial Vehicles (MAVs) have drawn attention to the aerospace community. With such autonomous flying platforms, it is possible to explore foreign extraterrestrial bodies in an efficient and faster manner than other robotic platforms, like rovers. In addition, they can be equipped with a variety of different sensors. Cameras are especially well suited, since they are light, energy-efficient and deliver a broad spectrum of information. Following the underlying terrain in a defined height is a fundamental task for any exploring MAV. To accomplish this, many systems possess a designated height sensor, which in most cases only delivers a single height estimation taken from nadir. In such a setup, the MAV is just adjusting its height based on the current height estimation and does not take any terrain lying ahead into account, which results in delayed height adjustments. In this paper, we propose a novel method based on a wide-angle stereo camera setup, which is attached to the MAV, to overcome such problems. Due to the wide vertical field of view, the vehicle is able to not only measure its current height, but also the terrain lying ahead. Therefore, the MAV is able to perform a better terrain following compared to other methods, which use just a single nadir height sample. Our algorithm only needs to take the depth image, calculated by the stereo cameras, and the estimated gravity vector into account. Therefore, our method is very fast and computationally efficient, compared to other methods, which build up an entire map beforehand. As a result, the procedure presented here is also suitable for tiny flying systems with low computational capabilities and memory resources. The terrain following algorithm runs in real-time and on board the system, and is therefore also suitable for confined environments, like caves, and where communication delays are present. We evaluate our method with simulated data and real tests on an MAV. To demonstrate that our method works in a variety of different terrains, we show experiments with different slopes and obstacles in the flight path. We also compare our method to a basic terrain following by using just a single height measurement in a more classical approach.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Integrated Innovative 3D Radiation Protection Fabric for Advanced Spacesuits and Systems Model-based Tools designed for the FACE™ Technical Standard, Editions 3.0 & 2.1 Can Adaptive Response and Evolution Make Survival of Extremophile Bacteria Possible on Mars? Initial Orbit Determination Using Simplex Fusion Headline-based visualization to prioritize events
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1