Enhanced Potential Field-Based Collision Avoidance for Unmanned Aerial Vehicles in a Dynamic Environment

Choi, Daegyun; Lee, Kyuman; Kim, Dong Hoon

doi:10.2514/6.2020-0487

Cited by 31 publications

(29 citation statements)

References 17 publications

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“…When |V Ob | = 0 coordinates of point P C were the same as the obstacle's P O , and distance ρ O = 0. If it was assumed that P C = P Ob , ρ O = 0 and |V Ob |=0, the repulsive potential function (11) would create a spherical repulsive force field around the obstacle. The main advantage of the multidimensional repulsive potential function was its flexibility.…”

Section: Resultsmentioning

confidence: 99%

“…Repulsive forces presented in Figure 4 are reverse gradients of the multidimensional repulsive potential function from (11), represented by the following equation:…”

Section: Design Of the Multidimensional Repulsive Potential Fieldmentioning

confidence: 99%

“…What is important, is that the presented algorithm provides a near-optimal collision-free trajectory. Furthermore, an optimal and collision-free trajectory was proposed in work [11], where an APF approach, called an "enhanced curl-free vector field" was described. In this method, for the repulsive potential field, one computes each angle between the velocity vectors of UAVs and the relative position vectors of moving obstacles to the UAVs.…”

Section: Introductionmentioning

confidence: 99%

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A New Multidimensional Repulsive Potential Field to Avoid Obstacles by Nonholonomic UAVs in Dynamic Environments

Kownacki

Ambroziak

2021

Sensors

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The ability of autonomous flight with obstacle avoidance should be a fundamental feature of all modern unmanned aerial vehicles (UAVs). The complexity and difficulty of such a task, however, significantly increase in cases combining moving obstacles and nonholonomic UAVs. Additionally, since they assume the symmetrical distribution of repulsive forces around obstacles, traditional repulsive potential fields are not well suited for nonholonomic vehicles. The limited maneuverability of these types of UAVs, including fixed-wing aircraft, requires consideration not only of their relative position, but also their speed as well as the direction in which the obstacles are moving. To address this issue, the following work presents a novel multidimensional repulsive potential field dedicated to nonholonomic UAVs. This field generates forces that repulse the UAV not from the obstacle’s geometrical center, but from areas immediately behind and in front of it located along a line defined by the obstacle’s velocity vector. The strength of the repulsive force depends on the UAV’s distance to the line representing the obstacle’s movement direction, distance to the obstacle along that line, and the relative speed between the UAV and the obstacle projected to the line, making the proposed repulsive potential field multidimensional. Numerical simulations presented within the paper prove the effectiveness of the proposed novel repulsive potential field in controlling the flight of nonholonomic UAVs.

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Section: Resultsmentioning

confidence: 99%

“…Repulsive forces presented in Figure 4 are reverse gradients of the multidimensional repulsive potential function from (11), represented by the following equation:…”

Section: Design Of the Multidimensional Repulsive Potential Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Multidimensional Repulsive Potential Field to Avoid Obstacles by Nonholonomic UAVs in Dynamic Environments

Kownacki

Ambroziak

2021

Sensors

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“…In [104], the authors proposed a novel artificial potential field approach called "enhanced curl-free vector field" for optimal collision free routes generation under dynamic conditions with multiple obstacles, where other UAVs are also considered as moving obstacles as well. Instead of utilising the conventional potential field, in this approach, enhanced curl-free vector field, i.e., conservative field, is used by generating the field around the obstacle and determining the field vectors, i.e., direction of the curl-free vector, based on the velocity vector of dynamic obstacles and the corresponding position vector's angle from UAV to the obstacle and the path angle of the UAV.…”

Section: B Force-field Methodsmentioning

confidence: 99%

Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches

et al. 2020

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Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable as possible, necessitating a comparative study of the recent work in this important area. The paper provides a comprehensive review of collision avoidance strategies used for unmanned vehicles, with the main emphasis on unmanned aerial vehicles (UAV). It is an in-depth survey of different collision avoidance techniques that are categorically explained along with a comparative analysis of the considered approaches w.r.t. different scenarios and technical aspects. This also includes a discussion on the use of different types of sensors for collision avoidance in the context of UAVs. INDEX TERMS autonomous aerial vehicles, autonomous vehicles, collision avoidance, active and passive sensors, optimisation-based, force-field based, sense and avoid, geometry based

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“…Embora existam diversas estratégias de prevenc ¸ão de colisão, segundo nosso conhecimento, nenhum trabalho avaliou essas técnicas no cenário de entrega com drones em que há pousos e decolagens e um número maior de drones. Além disso, a maioria dos trabalhos avalia colisões durante o vôo em cruzeiro, em que normalmente não há variac ¸ão de altura, reduzindo o problema de colisão a duas dimensões e não considerando colisões que podem ocorrer durante o pouso e decolagem ou testando apenas casos em duas dimensões [Yasin et al 2020, Gageik et al 2015, Choi and Kim 2020. Por fim, os resultados da literatura mostram que nenhuma técnica de prevenc ¸ão de colisão é capaz de evitar todas as colisões, sendo necessário agregar uma ou mais técnicas de prevenc ¸ão de colisão [Yasin et al 2020].…”

Section: Introduc ¸ãOunclassified

Prevenção de Colisões em Serviços de Entregas por Drones em Cidades Inteligentes

Oliveira

Bittencourt

Kamienski

2021

Anais Do v Workshop De Computação Urbana (CoUrb 2021)

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Os recentes avanços em veículos aéreos não tripulados (VANT), usualmente chamados de drones, aliados às novas tecnologias de comunicação e de inteligência artificial, estão possibilitando o desenvolvimento de serviços aéreos de entregas de mercadorias para um futuro próximo. No entanto, para que tais serviços avançados para cidades inteligentes se tornem realidade, é necessário garantir a segurança nas entregas. Particularmente, é necessário garantir que drones não colidam com outros drones, com outros objetos ou seres voadores, assim como com os vários obstáculos típicos de ambientes urbanos. Esse artigo propõe um cenário de serviço de entregas por drones em cidades inteligentes e avalia o número de drones que colidem sob três abordagens diferentes para a situação em que um drone se aproxima de outro: manter a rota original, efetuar um desvio aleatório e efetuar um desvio à direita, como na aviação. Os resultados mostram que os desvios podem manter ou eliminar o número de colisões para frotas com poucos drones, mas aumentam o número de colisões quando a densidade de drones aumenta. Investigamos o tempo de viagem dos drones para mostrar como cada abordagem se comporta e as posições das colisões para identificar a situação das colisões. A principal conclusão é que abordagens simples e ingênuas de desvio não garantem a evasão de colisões, indicando que estratégias mais sofisticadas devem ser aplicadas.

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Enhanced Potential Field-Based Collision Avoidance for Unmanned Aerial Vehicles in a Dynamic Environment

Cited by 31 publications

References 17 publications

A New Multidimensional Repulsive Potential Field to Avoid Obstacles by Nonholonomic UAVs in Dynamic Environments

A New Multidimensional Repulsive Potential Field to Avoid Obstacles by Nonholonomic UAVs in Dynamic Environments

Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches

Prevenção de Colisões em Serviços de Entregas por Drones em Cidades Inteligentes

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