Behavior-based decentralized approach for cooperative control of a multiple small scale unmanned helicopter

Kaliappan, Vishnu Kumar; Yong, Hanmaro; Dai, Min; Budiyono, Agung

doi:10.1109/isda.2011.6121654

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…The UAV must forecast and prevent potential threads while maneuvering. In some situations, the projected occurrence of obscurations can be prevented utilizing onboard data such as terrain height and several well-known threads [12]. An anonymous obstacle may occur in real-time circumstances; the algorithm should address these types of obstacles, even if they are small.…”

Section: Ruav Obstacle Detection and Avoidance Algorithmmentioning

confidence: 99%

“…The location of the RUAVs future north and south (hpf e , hpf n ) position is estimated using Eq. (12),…”

Section: Navigation and Guidance Lawmentioning

confidence: 99%

“…The usage of these vehicles was not only restricted to military applications. However, it is also employed for civil based applications such as cooperative fire detection [1,2] terrain mapping [3,4] autonomous sensor network assignment for intelligent city applications [5], Air quality measurements [6], smart farming [7,8], search and rescue [9], bridge crack detection [10], smart farming [11], cooperative task execution [12], package delivery [13] and so on. In the applications mentioned earlier, remote-based piloting is an option for largely open airspace.…”

Section: Introductionmentioning

confidence: 99%

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Steering Behavior-based Multiple RUAV Obstacle Avoidance Control

Kaliappan¹,

Nguyen²,

Dai³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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In recent years, the applications of rotorcraft-based unmanned aerial vehicles (RUAV) have increased rapidly. In particular, the integration of bioinspired techniques to enhance intelligence in coordinating multiple Rotorcraftbased Unmanned Aerial Vehicles (RUAVs) has been a focus of recent research and development. Due to the limitation in intelligence, these RUAVs are restricted in flying low altitude with high maneuverability. To make it possible, the RUAVs must have the ability to avoid both static and dynamic obstacles while operating at low altitudes. Therefore, developing a state-of-the-art intelligent control algorithm is necessary to avoid low altitude obstacles and coordinate without collision while executing the desired task. This paper proposes an Artificial Intelligence (AI) based steering behavior algorithm that generates a smooth trajectory by avoiding static and dynamic obstacles. The proposed method uses an obstacle detection algorithm (ODA) and obstacle avoidance algorithm (OAA). An obstacle detection algorithm is used to detect potential threats that fall in the course of flight while reaching the desired target, and obstacle avoidance algorithms use the steering behavior method to generate avoidance trajectory. A PC104 embedded boardbased HIL (Hardware in the Loop) simulation environment is developed to validate the proposed algorithm. The proposed algorithm is evaluated by experimenting with a variety of nontrivial scenarios involving static and dynamic obstacles.

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Section: Ruav Obstacle Detection and Avoidance Algorithmmentioning

confidence: 99%

“…The location of the RUAVs future north and south (hpf e , hpf n ) position is estimated using Eq. (12),…”

Section: Navigation and Guidance Lawmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Steering Behavior-based Multiple RUAV Obstacle Avoidance Control

Kaliappan¹,

Nguyen²,

Dai³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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“…This paper begins from the exposition multi flying vehicle research which have been published in recent years, for examples, , which uses multiple spacecraft to fly to the surveillance activities. The next, Kaliappan, et al (2011) examining models of mini multi helicopter is used for the purposes of search and surveillance. The next publication was done by Fink, et al (2011) who are working on controlling a flying robot picked up the goods together.…”

Section: Introductionmentioning

confidence: 99%

Control of multi flying vehicle which move in 3 dimensions to save fuel

Tjahjana¹,

Sasongko²

2014

ams

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The world of commercial and military aviation, as well as the world of transportation in general are unable to break away from the fuel. With the lack of fuel and increasingly expensive fuel prices in the world market, airlines are required to make innovations that fuel can be saved. The idea that an aircraft is flying with another aircraft to fly together in the save formation, sure is one of the alternative methods to save fuel. This paper is presented a moving plane space a real motion in three dimensions or spaces. Designing the control for each flying vehicle is carried out by optimal control theory and the simulation is done with matlab software. The results of this research are expected to provide the basics in trying to fly some airplanes together. How to fly an airplane simulations together with the airplane in the special formation, not always together from beginning to end, but from the initial position, the aircraft fly singly, and then start at a position already agreed do flew together in formation until the point a particular purpose, then the aircraft spread towards the ultimate goal of each plane.

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“…O problema de mínimo local, encontrado em tarefas de desviar de obstáculo, é solucionado por Zhang et al (2010) ao considerar somente o obstáculo mais próximo para gerar o comportamento de desvio. Em (Kaliappan et al, 2011), o controle de formação baseado na abordagem comportamental é aplicado em veículos aéreos, para que estes sobrevoem uma determinada região, mantendo, em média, uma mesma distância (com baixas variações) entre eles para tarefas de vigilância, resgate e exploração. A característica desfavorável dessa abordagem é a dificuldade em comprovar, matematicamente, a estabilidade da formação, o que a torna não confiável.…”

Section: Formação De Robôsunclassified

Sistemas bio-inspirados para coordenação de múltiplos robôs móveis

Calvo¹

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Agradeço a Deus pela grandiosa oportunidade que tem me concedido e pela fé e serenidade proporcionados nos momentos mais difíceis. À minha família que sempre esteve do meu lado nos momentos mais difíceis. Meus pais, Milton e Helena, e meus irmãos, Fabio e Fernando. Pessoas que me ajudaram em todos os sentidos, e apoiando todo o tempo que estive longe de casa. Devo muito a eles, pela atenção e paciência. À minha noiva, Dayane, pela sua compreensão e infindável paciência durante o período que estive ausente por me dedicar ao desenvolvimento deste trabalho, pelo companherismo e apoio em todos os momentos. Agradeço a Profa. Dra. Roseli pelo esforço sem medida em me orientar, sempre disposta a ajudar. Agradeço pela confiança depositada, pela liberdade dada para trabalhar e pelos ensinamentos durante esse período de doutorado. Ao Prof. Dr. Maurício Figueiredo pelo apoio, por ter me iniciado nessa caminhada. Tudo o que eu obtive devo às suas conversas, conselhos profissionais e dedicação em me apoiar nas minhas decisões. Ao Prof. Dr. Denis F. Wolf e ao amigo Gustavo Pessin por indicarem a plataforma Player/Stage e pelos ensinamentos dos primeiros passos nesta ferramenta, fundamental para a obtenção dos resultados deste trabalho. Ao Prof. Dr. Roland Siegwart por ter me recebido na Eidgenössische Technische Hochschule Zürich, Suíça, durante o período de doutorado sanduíche, ao Prof. Dr. Dizan Vasquez e ao seu aluno de doutorado Andreas Breitenmoser por inúmeras reuniões de onde surgiram ideias que foram essenciais para o desenvolvimento deste trabalho.

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Behavior-based decentralized approach for cooperative control of a multiple small scale unmanned helicopter

Cited by 7 publications

References 7 publications

Steering Behavior-based Multiple RUAV Obstacle Avoidance Control

Steering Behavior-based Multiple RUAV Obstacle Avoidance Control

Control of multi flying vehicle which move in 3 dimensions to save fuel

Sistemas bio-inspirados para coordenação de múltiplos robôs móveis

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