Path Planning for UAVs for Maximum Information Collection

Ergezer, Halit; Leblebi̇ci̇oğlu, Kemal

doi:10.1109/taes.2013.6404117

Cited by 81 publications

(50 citation statements)

References 17 publications

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“…Sampling based algorithms [1], graph based search algorithms [2,3], mathematic model based algorithms [4,5], and bioinspired algorithms [6][7][8] are the fundamental families of path planning algorithms [9]. Most of the path planning solutions were originally developed for 2D problems and then extended to the third dimension, thus increasing the complexity of the approach and its computational cost.…”

Section: Introductionmentioning

confidence: 99%

Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

Benzaid

Marie

Mansouri

et al. 2018

Journal of Robotics

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This paper introduces an original 3D path planning approach for Unmanned Aerial Vehicle (UAV) applications. More specifically, the core idea is to generate a smooth and collision-free path with respect to the vehicle dimension. Given a 3D grid representation of the environment, the Generalized Voronoi Graph (GVG) is first approximated using a filtered medial surface (FMS) algorithm on the corresponding navigable space. Based on an efficient pruning criterion, the produced FMS excludes GVG portions corresponding to narrow passages unfitting safe UAV navigation constraints, and thus it defines a set of guaranteed safe trajectories within the environment. Given a set of starting and destination coordinates, an adapted A-star algorithm is then applied to compute the shortest path on the FMS. Finally, an optimization process ensures the smoothness of the final path by fitting a set of 3D Bézier curves to the initial path. For a comparative study, the A-star algorithm is applied directly on the input environment representation and relevant comparative criteria are defined to assert the proposed approach using simulation results.

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Section: Introductionmentioning

confidence: 99%

Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

Benzaid

Marie

Mansouri

et al. 2018

Journal of Robotics

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“…Therefore, the USV itself and the ground control station (GCS) where the remotely situated human operators are controlling the USV have to be concurrently designed and considered in terms of how to reach the intended functions and performance levels for the USVs [8]. In this regards, according to our initial study, the majority of the USVs that have been developed by many nations resemble each other as to the vehicle shape, the operating methods, and the missions that are being carried out [9] [10]. The purpose of this paper is, therefore, to investigate the recently technological development of USVs and identify the concept of USV operations.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Design Directions for Unmanned Surface Vehicles (USVs)

Heo¹,

Kim²,

Kwon³

2017

JCC

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In recent years, because of the development of marine military science technology, there is a growing interest in the unmanned systems throughout the world. Also, the demand of Unmanned Surface Vehicles (USVs) which can be autonomously operated without the operator intervention is increasing dramatically. The growing interests lie in the facts that those USVs can be manufactured at much lower costs, and can be operated without the human fatigue, while can be sent to the hostile or quite dangerous areas that are inherently unhealthy for human operators. The utilization and the deployment of such vessels will continue to grow in the future. In this paper, along with the technological development of unmanned surface vehicles, we investigate and analyze the cases of already developed platforms and identify the trends of the technological advances. Additionally, we suggest the future directions of development.

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“…The rapidly-exploring random-tree (RRT) method has been applied to the path planning problem of indoor robots and mini UAVs [6][7][8]. Genetic algorithms (GA) are used to solve the travelling salesman problems related to UAVs, such as maximum information collection [9]. The evolutionary algorithm (EA) is used for multi-constraint route planning in a simulation scenario [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Unmanned Aerial Vehicle Route Planning in the Presence of a Threat Environment Based on a Virtual Globe Platform

Zhang

Liu

et al. 2016

IJGI

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Route planning is a key technology for an unmanned aerial vehicle (UAV) to fly reliably and safely in the presence of a threat environment. Existing route planning methods are mainly based on the simulation scene, whereas approaches based on the virtual globe platform have rarely been reported. In this paper, a new planning space for the virtual globe and the planner is proposed and a common threat model is constructed for threats including a no-fly zone, hazardous weather, radar coverage area, missile killing zone and dynamic threats. Additionally, an improved ant colony optimization (ACO) algorithm is developed to enhance route planning efficiency and terrain masking ability. Our route planning methods are optimized on the virtual globe platform for practicability. A route planning system and six types of planners were developed and implemented on the virtual globe platform. Finally, our evaluation results demonstrate that our optimum planner has better performance in terms of fuel consumption, terrain masking, and risk avoidance. Experiments also demonstrate that the method and system described in this paper can be used to perform global route planning and mission operations.

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Path Planning for UAVs for Maximum Information Collection

Cited by 81 publications

References 17 publications

Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

Analysis of Design Directions for Unmanned Surface Vehicles (USVs)

Unmanned Aerial Vehicle Route Planning in the Presence of a Threat Environment Based on a Virtual Globe Platform

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