Build Your Own Quadrotor: Open-Source Projects on Unmanned Aerial Vehicles

Lim, Hadyanto; Park, Jaemann; Lee, Daewon; Kim, H. J.

doi:10.1109/mra.2012.2205629

Cited by 257 publications

(102 citation statements)

References 17 publications

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“…Multiple commercial and open-projects exist that aim to develop complete software architectures (see [14] for a complete survey). To the best of the author's knowledge, the most well-known open-source commercial projects are the "PX4 Flight Stack 1 ", and the "APM Flight Stack 2 ".…”

Section: Introductionmentioning

confidence: 99%

AEROSTACK: An architecture and open-source software framework for aerial robotics

Sánchez-López

Fernández

Bavle

et al. 2016

2016 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-To simplify the usage of the Unmanned Aerial Systems (UAS), extending their use to a great number of applications, fully autonomous operation is needed. There are many open-source architecture frameworks for UAS that claim the autonomous operation of UAS, but they still have two main open issues: (1) level of autonomy, being in most of the cases limited and (2) versatility, being most of them designed specifically for some applications or aerial platforms.As a response to these needs and issues, this paper presents Aerostack, a system architecture and open-source multi-purpose software framework for autonomous multi-UAS operation. To provide higher degrees of autonomy, Aerostack's system architecture integrates state of the art concepts of intelligent, cognitive and social robotics, based on five layers: reactive, executive, deliberative, reflective, and social. To be a highly versatile practical solution, Aerostack's open-source software framework includes the main components to execute the architecture for fully autonomous missions of swarms of UAS; a collection of ready-to-use and flight proven modular components that can be reused by the users and developers; and compatibility with five well known aerial platforms, as well as a high number of sensors.Aerostack has been validated during three years by its successful use on many research projects, international competitions and exhibitions. To corroborate this fact, this paper also presents Aerostack carrying out a fictional fully autonomous indoors search and rescue mission.

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Section: Introductionmentioning

confidence: 99%

AEROSTACK: An architecture and open-source software framework for aerial robotics

Sánchez-López

Fernández

Bavle

et al. 2016

2016 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…These tasks are already accomplished by vision-based robots, which are nowadays built with inexpensive equipment and have an easy maintenance. Several techniques to endow vehicles with vision-based control can be found in (Güzel, 2013;Bertozzi & Broggi, 1997;Tisdale, et al, 2009;Carloni, et al, 2013;Yunji, et al, 2013;Ivancsits & Lee, 2013;Lim, et al, 2012;Mahony, et al, 2012;Guillet, et al, 2014;Mcgill & Taylor, 2011). They enable object detection, path orientation and distance control.…”

Section: Introductionmentioning

confidence: 99%

“…For example, aircraft fuselage (Tisdale, et al, 2009;Kendoul, et al, 2009), helicopters (Yunji, et al, 2013;Ivancsits & Lee, 2013), quadmotors (Carloni, et al, 2013;Ivancsits & Lee, 2013;Lim, et al, 2012;Mahony, et al, 2012;Frew, et al, 2004), road robots (Bertozzi & Broggi, 1997;Guillet, et al, 2014;) and flying simulator games (Neto & Campos, 2009;Neto, et al, 2011) use Dubin's Path Waypoints (Dubins, 1957). All these vehicles use different approaches of location and orientation methods with techniques that either focus on the odometer or on the accelerometer, or even on the GPS itself.…”

Section: Introductionmentioning

confidence: 99%

“…These different approaches make unmanned vehicles over uncovered areas render different mappings. See Güzel, 2013;Bertozzi & Broggi, 1997;Tisdale, et al, 2009;Carloni, et al, 2013;Yunji, et al, 2013;Ivancsits & Lee, 2013;Lim, et al, 2012;Mahony, et al, 2012) for an overview. Some related to projects aim at a geographical image mapping that gives relevant data to agricultural activity (Guillet, 2014;Medeiros, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Generating Road Network Graph with Vision-Based Unmanned Vehicle

Yano

Zampirolli

2017

IJURCA

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This work has undergone a double-blind review by a minimum of two faculty members from institutions of higher learning from around the world. The faculty reviewers have expertise in disciplines closely related to those represented by this work. If possible, the work was also reviewed by undergraduates in collaboration with the faculty reviewers. AbstractWith the advancement of technology and its cheapness, robotic vehicles have gained a large number of applications. The spread of their use is growing also because they are getting smaller, lighter and easier to build. In this paper we present a simple and effective way to map a road network with the help of a driverless vehicle. Our approach consists of only three parts: vision-segmentation, angle variation and travelled distance. A video camera attached to a Lego® NXT Mindstorm vehicle guides it by image segmentation using Matlab® Image processing toolbox, along a road network, in which is represented by black tape over a white floor. The algorithm makes the vehicle travel all over the road memorizing main coordinates to identify all crossroads by keeping track of the travelled distance and the current angle. The crossroads and road's end are the nodes of the graph. After several simulations have been performed, the modelling proved to be successful in that small scale approach. Consequently, there are good chances that driverless cars and UAVs also make use of the strategies to map route networks accordingly. The algorithm presented in this paper is useful when there is no localization signal such as GPS, for example, navigation on water, tunnels, inside buildings, among others.

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“…서 론 쿼드로터(quadrotor)는 기구학적으로 구조가 간단하 고 비교적 안정적인 대표 무인 비행체로서 최근 군사 용뿐만 아니라 민간/산업용으로 보급이 확대됨에 따라 관련 연구 및 개발이 활발히 진행되고 있다 [1] . 쿼드로 터의 자세 제어와 관련해서는 제어 안정성 및 정확성 향상을 목표로 다양한 연구가 진행되었는데 [2] , 일반적 인 PID 제어 외에 비선형 제어 및 퍼지 제어를 적용한 연구도 소개되었다 [3～4] .…”

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Geomagnetic Sensor Compensation and Sensor Fusion for Quadrotor Heading Direction Control

Lee¹,

Ryoo²

2016

Journal of the Institute of Electronics and Information Enginee

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Geomagnetic sensors are widely utilized for sensing heading direction of quadrotors. However, measurement from a geomagnetic sensor is easily corrupted by environmental magnetic field interference and roll/pitch directional motion. In this paper, a measurement method of a quadrotor heading direction is proposed for application to yaw attitude control. In order to eliminate roll/pitch directional motion effect, the geomagnetic sensor data is compensated using the roll/pitch angles measured for stabilization control. In addition, yaw-directional angular velocity data from a gyroscope sensor is fused with the geomagnetic sensor data using a complementary filter which is a simple and intuitive sensor fusion method. The proposed method is applied to experiments, and the results are presented to prove validity and effectiveness of the proposed method.

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Build Your Own Quadrotor: Open-Source Projects on Unmanned Aerial Vehicles

Cited by 257 publications

References 17 publications

AEROSTACK: An architecture and open-source software framework for aerial robotics

AEROSTACK: An architecture and open-source software framework for aerial robotics

Generating Road Network Graph with Vision-Based Unmanned Vehicle

Geomagnetic Sensor Compensation and Sensor Fusion for Quadrotor Heading Direction Control

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