A 3D Frontier-Based Exploration Tool for MAVs

Zhu, Changfeng; Ding, Rong; Lin, Mengxiang; Wu, Yuanyuan

doi:10.1109/ictai.2015.60

Cited by 57 publications

(31 citation statements)

References 7 publications

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“…Considering 3D scenarios, a direct extension of a frontier-based method has been presented in [8]. In three dimensions, even the simple process of identifying the frontiers during the exploration becomes more challenging and costly and has been a subject of research [40]. In [32], the authors propose an analysis of the traversability of the scanned area and an improved K-means algorithms to reduce the dimension of frontiers in the map and improve the efficiency of the results but, contrary to our case, the exploration is carried out by ground robots.…”

Section: Autonomous Explorationmentioning

confidence: 99%

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

Renzaglia

Dibangoye

Doze

et al. 2020

J Intell Robot Syst

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This paper studies the problems of static coverage and autonomous exploration of unknown three-dimensional environments with a team of cooperating aerial vehicles. Although these tasks are usually considered separately in the literature, we propose a common framework where both problems are formulated as the maximization of online acquired information via the definition of single-robot optimization functions, which differs only slightly in the two cases to take into account the static and dynamic nature of coverage and exploration respectively. A common derivative-free approach based on a stochastic approximation of these functions and their successive optimization is proposed, resulting in a fast and decentralized solution. The locality of this methodology limits however this solution to have local optimality guarantees and specific additional layers are proposed for the two problems to improve the final performance. Specifically, a Voronoi-based initialization step is added for the coverage problem and a combination with a frontier-based approach is proposed for the exploration case. The resulting algorithms are finally tested in simulations and compared with possible alternatives.

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Section: Autonomous Explorationmentioning

confidence: 99%

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

Renzaglia

Dibangoye

Doze

et al. 2020

J Intell Robot Syst

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“…Among them, random explorations, where a robot explores random points around itself within a given distance, have been proposed. Frontier features exploration where a robot explores unknown areas nearby already explored areas have been also published [1], [2]. Finally, human directed exploration where the human directs the robot for exploration have been presented.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, human directed exploration where the human directs the robot for exploration have been presented. In this paper, a focus on frontier-based exploration [1], [2] is proposed. The exploration strategy can also be combined with coverage constraints [3], where both the target and the path to reach it are processed.…”

Section: Related Workmentioning

confidence: 99%

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Cooperative exploration strategy for micro-aerial vehicles fleet

Mahdoui¹,

Frémont²,

Natalizio³

2017

2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots data exchange. The novelty comes from the exchange of the frontiers points instead of maps, which allows to reduce computation and data amount within the network. The proposed system has been implemented and tested under ROS using the Gazebo simulator. The results demonstrate that the proposed navigation strategy efficiently spreads robots over the environment for a faster exploration.

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“…Los mapas métricos tienen la ventaja de poder representar obstáculos y escenarios más complejos. En los mismos, se puede aplicar el concepto de fronteras de exploración tanto a 2D (Yamauchi, 1997), como a 3D (Zhu, Ding, Lin, & Wu, 2015), donde se obtienen buenos resultados y el problema pasa a ser el de elegir la mejor frontera a visitar. Estos mapas, por sus características, rápidamente ocupan gran cantidad de memoria, y no son fácilmente aplicables a sistemas embebidos, en particular aquellos con las restricciones de vuelo para MAVs (Ramaithitima, Whitzer, Bhattacharya, & Kumar, 2016).…”

Section: Introductionunclassified

Consideraciones de implementación para algoritmos de exploración robótica en plataformas de procesamiento limitado

Nievas

Araguás²,

Paz³

2020

AJEA

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El proceso de exploración de un ambiente no estructurado presenta numerosas dificultades a la hora de implementar soluciones en plataformas con capacidades de procesamiento limitado. En el presente trabajo se mencionan las técnicas de exploración comúnmente utilizadas y consideraciones para su implementación en sistemas de hardware limitado. Se analizan problemas encontrados con mapas topológicos, en particular aquellos en forma de árbol durante la exploración. También se exponen resultados obtenidos con la plataforma Jetson Nano para procesar una nube de puntos generada mediante la cámara Intel Realsense D435. Se explican detalles a tener en cuenta con la velocidad de memoria de la misma.

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A 3D Frontier-Based Exploration Tool for MAVs

Cited by 57 publications

References 7 publications

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

Cooperative exploration strategy for micro-aerial vehicles fleet

Consideraciones de implementación para algoritmos de exploración robótica en plataformas de procesamiento limitado

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