Multi-Camera Networks for Coverage Control of Drones

Huang, Sunan; Teo, Rodney; Leong, Wai Lun

doi:10.3390/drones6030067

Cited by 6 publications

(5 citation statements)

References 18 publications

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“…An area coverage task [9][10][11] assigned to multiple agents would involve the execution of a distributed area coverage algorithm with message exchanges between assigned agents such that they spread out within the designated area in an optimal manner.…”

Section: Task Executionmentioning

confidence: 99%

“…The use of unmanned aerial vehicles (UAVs) or drones have increased in the recent years. From the use of single UAVs for inspection, surveillance, mapping, and 3D modeling [1][2][3][4][5], we now have multi-agent algorithms implemented in flying ad-hoc networks (FANETs) [6] for cooperative coverage [7][8][9][10][11], surveillance, and target tracking [12,13]. The trend suggests that large numbers of cost-effective agents using a bottom-up approach and simple rules modeled after social insects can result in emergent behaviour and swarm intelligence that exhibit flexible, robust, decentralized and self-organizing properties [14].…”

Section: Introductionmentioning

confidence: 99%

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Scalable Task Allocation with Communications Connectivity for Flying Ad-Hoc Networks

Leong,

Cao,

Teo

2024

J Intell Robot Syst

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Task allocation enables heterogeneous agents to execute heterogeneous tasks in the domain of unmanned aerial vehicles, while responding to dynamic changes in the environment and available resources to complete complex, multi-objective missions, leading to swarm intelligence. We propose a bio-inspired approach using digital pheromones to perform scalable task allocation when the number of agents, tasks, and the diameter of the communications graph increase. The resulting emergent behaviour also enables idle agents in the swarm to provide periodic or continuous connectivity between disconnected parts of the swarm. We validate our results through simulation and demonstrate the feasibility of our approach by applying it to the 3D coverage and patrol problem.

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Section: Task Executionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scalable Task Allocation with Communications Connectivity for Flying Ad-Hoc Networks

Leong,

Cao,

Teo

2024

J Intell Robot Syst

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“…Using small unmanned aerial systems for quick, wide area coverage (WAC) mapping is becoming increasingly popular. 2 Implementing multi-camera systems for target detection and recognition purposes can have a large benefit over gimbal systems. 3 The probability of recognizing an object is calculated by using the targeting task performance (TTP) metric.…”

Section: Introductionmentioning

confidence: 99%

Visible, SWIR, and LWIR drone wide area coverage sensor systems

Leslie,

Chau,

Watson

et al. 2024

Opt. Eng.

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Small unmanned aerial systems provide a versatile platform for covering large areas quickly. By adding sensors to drones, imagery of large areas can be taken for a variety of applications. Traditionally, single fixed staring systems or gimballed sensors are used to take this imagery. Both options require a compromise between field of view (FOV), resolution, scanning speed, and flight path to properly perform the desired task. If more than one sensor is integrated onto the drone, a wide FOV can be covered without a scanning gimbal and obtain higher resolution than a traditional wide FOV staring system. Presented is a multi-camera design approach based on a constraining ground sample distance for a wide area coverage (WAC) system. This design approach can be used for any imaging bands. A figure of merit (FoM) is derived to quantify and compare the performance of the WAC systems in the visible (0.4 to 0.7 μm), short wave infrared (1.0 to 1.7 μm), and longwave infrared (8 to 14 μm) for both good and bad visibility conditions. The performance of three optimized and fabricated WAC systems is compared and tested through the FoM and flight testing.

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“…Currently photogrammetry is a popular area of study of adding many cheap sensors to sUAS's to map out areas with higher resolution 2 and even create 3D models of areas using the stereopairs of imagery 3 . Using sUAS for wide area coverage mapping quickly is becoming an increasingly popular field 4 . The computational power needed to create stitched imagery of large areas and use the data for various purposes is easy to obtain.…”

Section: Introductionmentioning

confidence: 99%

Visible, SWIR, and LWIR drone wide area coverage sensor systems

Leslie,

Chau,

Watson

et al. 2023

Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV

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Small Unmanned Aerial Systems (sUAS) provide a versatile platform for covering large areas quickly. By adding sensors to these drones, imagery of large areas can be taken for a variety of applications. Traditionally, a fixed staring system or a gimballed sensor is used to take this imagery. Both options require a compromise between field of view (FOV), resolution, scanning speed and flight path to properly perform the task at hand. With more than one type of sensing, additional information can be collected about imaged environments. If more than one sensor is integrated onto the drone, a wide FOV can still be covered without a scanning gimbal and with higher resolution than a traditional wide FOV system. Presented is a multi-camera, multi-wavelength design approach based on a constraining ground sample distance (GSD) for a wide area coverage (WAC) system. A figure of merit (FoM) is created to quantify and compare the performance of the WAC systems in the visible (0.4-0.7um), short wave infrared (1.0-1.7um) and longwave infrared (8-14um) in both good and bad visibility conditions. The performance of three optimized and fabricated WAC systems are compared and tested. The testing results of the flown fabricated systems show that the design approach described delivers the expected results.

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Multi-Camera Networks for Coverage Control of Drones

Cited by 6 publications

References 18 publications

Scalable Task Allocation with Communications Connectivity for Flying Ad-Hoc Networks

Scalable Task Allocation with Communications Connectivity for Flying Ad-Hoc Networks

Visible, SWIR, and LWIR drone wide area coverage sensor systems

Visible, SWIR, and LWIR drone wide area coverage sensor systems

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