Autonomous flight and obstacle avoidance of a quadrotor by monocular SLAM

Esrafilian, Omid; Taghirad, Hamid D.

doi:10.1109/icrom.2016.7886853

Cited by 49 publications

(18 citation statements)

References 5 publications

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“…The various sensors and techniques used in automobiles like car to unmanned air vehicles have been given in Connolly (2007). A collision avoidance scheme is presented using Aerial Quadrotor (drone) (Esrafilian and Taghirad, 2016). Video streams obtained using front camera of drone and navigation data measured by Aerial Quadrotor drone is transmitted to ground placed laptop through wireless network connection.…”

Section: Uav Sensing Methodsmentioning

confidence: 99%

UAV attitude estimation based on the dual filtering methods

Zhuang

Guo

Raj

et al. 2018

IJIUS

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Purpose A toy UAV performs tumbling, rolling, racing and other complex activities. It is based on low-cost hardware and hence requires a better algorithm to estimate the attitudes more accurately with low power consumption. The proposed technique based on optimized Madgwick filter and moving average filter (MAF) ensures improved convergence speed in estimating the attitude, achieves higher accuracy and provides robustness and stability of the toy UAV. The paper aims to discuss this issue. Design/methodology/approach Traditional methods are prone to problems such as slow convergence speed and errors in calculation of the attitude angles. These errors cause the vehicle to drift and tremble, thus affecting the overall stability of the vehicle. The proposed method combines the features of optimized Madgwick filter and MAF to provide better accuracy, achieved through the fusion of gyroscope and accelerometer data, and zero correction to eliminate the random drift error of the gyroscope and removal of high-frequency interference by MAF of the accelerometer data. The experimental results on actual flight data showed that the method was better than the conventional Madgwick and Mahony complementary filters. Findings The performance of the proposed method was analyzed by estimating the pitch and roll angles under the static and dynamic condition of the toy UAV. The results were compared with two traditional methods: Madgwick and Mahony complement filter. In the static condition, the variance and average error while estimating the attitudes was comparatively lower than the traditional method. For the dynamic conditions, the convergence time to achieve a prescribed swing angle was again lower than the traditional method. From these two experiments, it can be seen that the proposed method provides better attitude estimation at lower computation time. Originality/value The proposed method combines the optimized Madgwick filter and MAF to accuracy estimate the attitude of toy UAV. The algorithm mainly suits the toy UAVs which are based on low-cost hardware and require better control systems to ensure stability of the vehicle. The experimental results on real flight data illustrate that the method not only improves the convergence speed in estimating the attitude angle for large maneuvers of the toy UAV, but also achieves higher accuracy in the attitude estimation, thus ensuring the robustness and stability of the UAV.

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Section: Uav Sensing Methodsmentioning

confidence: 99%

UAV attitude estimation based on the dual filtering methods

Zhuang

Guo

Raj

et al. 2018

IJIUS

View full text Add to dashboard Cite

show abstract

“…The adaptation function of the path is evaluated to be effective with real-time performance in GPSdenied environments. Esrafilian and Taghirad (2016) put forward a method based on oriented fast and rotated brief SLAM (ORB-SLAM). First, it processes video data, by computing 3D locations of the UAV and generating a sparse point cloud map.…”

Section: Intelligent Algorithmsmentioning

confidence: 99%

A survey on vision-based UAV navigation

Xue

Xia

et al. 2018

Geo-spatial Information Science

304

122

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Research on unmanned aerial vehicles (UAV) has been increasingly popular in the past decades, and UAVs have been widely used in industrial inspection, remote sensing for mapping & surveying, rescuing, and so on. Nevertheless, the limited autonomous navigation capability severely hampers the application of UAVs in complex environments, such as GPS-denied areas. Previously, researchers mainly focused on the use of laser or radar sensors for UAV navigation. With the rapid development of computer vision, vision-based methods, which utilize cheaper and more flexible visual sensors, have shown great advantages in the field of UAV navigation. The purpose of this article is to present a comprehensive literature review of the vision-based methods for UAV navigation. Specifically on visual localization and mapping, obstacle avoidance and path planning, which compose the essential parts of visual navigation. Furthermore, throughout this article, we will have an insight into the prospect of the UAV navigation and the challenges to be faced.

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“…In this method the MAV's trajectory is evaluated in real-time and is based on LSD-SLAM. A self-flying and hindrance handling system built on monocular vision is presented in [39]. A ground station laptop receives navigation data and camera video from the drone wirelessly.…”

Section: Communicationmentioning

confidence: 99%

Aerial and Under-water Dronal Communication: Potentials, Issues and Vulnerabilities

Srinivasan*¹,

Ramaneswaran²,

Subramanian³

et al. 2019

IJITEE

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The use of UAVs has been on the rise since the past decade. These UAVs are very versatile and can be applied to several fields ranging from agriculture to military reconnaissance. Due to the immense functionality of the UAVs, it has now become a very popular topic in Research. With the advent of Deep Learning and Machine Learning the autonomous navigation functionalities have been improved but it still poses a challenge as navigating a drone involves the integration of its software and hardware functionalities. This paper reviews both indoor and outdoor navigation. Topics in navigation such as Control, Hardware, Algorithms, Path-Planning, and communication are touched upon in this paper. The paper also presents a discussion on the Navigation of UAVs using visionbased technologies, this technology encompasses the use of various sensors and cameras and integrate it with the navigation system of the UAV to ensure the success of UAV’s operation. UAVs play a pivotal role in networking, many applications have been developed which have UAVs as an important component in them. Their applications include Urban computing, Internet of Things, Ubiquitous Computing to name a few. Safely operating a UAV as a network node is not a simple task, these nodes are prone to various types of attacks. A new type of attack introduced in this paper is termed as “Coagulation Attack”. This attack gets its name from the coagulation property of fluids wherein fluids clot and their particles settle down. This paper explores the concept, issues, challenges and research aspects of Coagulation attack. This paper also introduces the concept of Underwater Wireless Communication. On a planet where 70% of the surface is covered in water, UWC has a lot of potentials to be exploited. Moreover UWC is critical in many key areas of Maritime research, commerce, and surveillance. UWC is used for experimental observation, data collection and analysis, underwater navigation, disaster prevention and early detection warning of a tsunami. In addition, we summarize emerging technologies in the UWC, future research directions and recommendations using fifth-generation (5G) communication techniques.

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Autonomous flight and obstacle avoidance of a quadrotor by monocular SLAM

Cited by 49 publications

References 5 publications

UAV attitude estimation based on the dual filtering methods

UAV attitude estimation based on the dual filtering methods

A survey on vision-based UAV navigation

Aerial and Under-water Dronal Communication: Potentials, Issues and Vulnerabilities

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