Autonomous Routing and Power Management of Drones in GPS-Denied Environments through Dijkstra Algorithm

Mirzaeinia, Amir; Shahmoradi, Javad; Roghanchi, Pedram; Hassanalian, Mostafa

doi:10.2514/6.2019-4462

Cited by 17 publications

(7 citation statements)

References 29 publications

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“…Despite advancements in drone technology, the use of drones in underground mines has been limited [63]. This is because the application of drones in underground mines is challenging.…”

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

“…Confined space, reduced visibility, air velocity, dust concentration, and lack of wireless communication system make it a difficult task for an operator to fly a drone in underground working areas. Furthermore, access to unreachable and dangerous locations in underground mines is practically impossible for a drone operator [63].…”

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

“…Drones in underground mines have numerous potential applications in health and safety. These applications include surface roughness mapping, rock mass stability analysis, ventilation modeling, hazardous gas detection, and leakage monitoring [32,[63][64][65][66][67][68]].…”

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

“…The visibility of people and objects in real-time is important to avoid accidents. However, there are many circumstances in which visibility is not sufficient to proceed with a mission using a drone [63,89].…”

Section: Challenges In Using Drones In Underground Minesmentioning

confidence: 99%

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A Comprehensive Review of Applications of Drone Technology in the Mining Industry

Shahmoradi

Talebi

Roghanchi

et al. 2020

Drones

Self Cite

229

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This paper aims to provide a comprehensive review of the current state of drone technology and its applications in the mining industry. The mining industry has shown increased interest in the use of drones for routine operations. These applications include 3D mapping of the mine environment, ore control, rock discontinuities mapping, postblast rock fragmentation measurements, and tailing stability monitoring, to name a few. The article offers a review of drone types, specifications, and applications of commercially available drones for mining applications. Finally, the research needs for the design and implementation of drones for underground mining applications are discussed.

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“…Despite advancements in drone technology, the use of drones in underground mines has been limited [63]. This is because the application of drones in underground mines is challenging.…”

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

Section: Application Of Arones In Underground Minesmentioning

confidence: 99%

Section: Challenges In Using Drones In Underground Minesmentioning

confidence: 99%

See 2 more Smart Citations

A Comprehensive Review of Applications of Drone Technology in the Mining Industry

Shahmoradi

Talebi

Roghanchi

et al. 2020

Drones

Self Cite

229

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“…Sometimes applying multiple drones to perform a defined mission is more efficient than having one drone [26][27][28][29][30] . The flight of multiple drones which is inspired by nature is called swarming.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Loader and tester swarming drones for cellular phone network loading and field test: non-stochastic particle swarm optimization

et al. 2019

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Cellular network operators have problems to test their network without affecting their user experience. Testing network performance in a loaded situation is a challenge for the network operator because network performance differs when it has more load on the radio access part. Therefore, in this paper, deploying swarming drones is proposed to load the cellular network and scan/test the network performance more realistically. Besides, manual swarming drone navigation is not efficient enough to detect problematic regions. Hence, particle swarm optimization is proposed to be deployed on swarming drone to find the regions where there are performance issues. Swarming drone communications helps to deploy the particle swarm optimization (PSO) method on them. Loading and testing swarm separation help to have almost non-stochastic received signal level as an objective function. Moreover, there are some situations that more than one network parameter should be used to find a problematic region in the cellular network. It is also proposed to apply multi-objective PSO to find more multi-parameter network optimization at the same time.Cellular networks have been growing rapidly over the last few decades. This technology is exceptionally beloved these days because people can be connected as they move around anyplace. Wireless communication was developed even before cellular networks, but radio communication always suffers from resource limitation (frequency spectrum as the main resource). Resource limitation was the main motivation to propose resource reuse in cellular networks [1] . For example, if a frequency band is used in a certain cell in the cellular network to cover a particular area, it also can be used in another cell which is farther in the distance from the first one. The idea of resource reuse helps to increase the number of users being serviced. This idea of resource reuse is the main difference between cellular network technology and other radio networks. However, this adds to the complexity of fine-tuning of the network to achieve high-performance cells. The reason is that radio interference can decrease the quality of service in these networks. First-generation cellular networks started in the 1980s as analog radio communication. Later on, the 2G network was commercially launched around the

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Path Planning and Landing for Unmanned Aerial Vehicles Using AI

Politi

Garyfallou

Panagiotopoulos

et al. 2022

Lecture Notes in Networks and Systems

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Autonomous Routing and Power Management of Drones in GPS-Denied Environments through Dijkstra Algorithm

Cited by 17 publications

References 29 publications

A Comprehensive Review of Applications of Drone Technology in the Mining Industry

A Comprehensive Review of Applications of Drone Technology in the Mining Industry

Loader and tester swarming drones for cellular phone network loading and field test: non-stochastic particle swarm optimization

Path Planning and Landing for Unmanned Aerial Vehicles Using AI

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