Scientific Publications

@inproceedings{imav2024-39:k_meier_et_al,

title = {WildBridge: Conservation Software for Animal Localisation using Commercial Drones},

author = {Kilian Meier and Arthur Richards and Matthew Watson and Caspian Johnson and Duncan Hine and Tom Richardson and Guy Maalouf},

editor = {T. Richardson},

url = {http://www.imavs.org/papers/2024/39.pdf},

year  = {2024},

date = {2024-09-16},

urldate = {2024-09-16},

booktitle = {15th annual International Micro Air Vehicle Conference and Competition},

pages = {324–333},

address = {Bristol, United Kingdom},

note = {Paper no. IMAV2024-39},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{imav2024-38:e_rolland_et_al,

title = {Drone Swarms for Animal Monitoring: A Method for Collecting High-Quality Multi-Perspective Data},

author = {Edouard Rolland and Kasper Grøntved and Lucie Laporte-Devylder and Jenna Kline and Ulrik Lundquist and Anders Christensen},

editor = {T. Richardson},

url = {http://www.imavs.org/papers/2024/38.pdf},

year  = {2024},

date = {2024-09-16},

urldate = {2024-09-16},

booktitle = {15th annual International Micro Air Vehicle Conference and Competition},

pages = {316–323},

address = {Bristol, United Kingdom},

note = {Paper no. IMAV2024-38},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{imav2024-36:v_shukla_et_al,

title = {Exploring the potential of UAV collaborative 3D mapping in Kenyan savanna for wildlife research},

author = {Vandita Shukla and Luca Morelli and Pawel Trybala and Fabio Remondino and Wentian Gan and Yifei Yu and Xin Wang},

editor = {T. Richardson},

url = {http://www.imavs.org/papers/2024/36.pdf},

year  = {2024},

date = {2024-09-16},

urldate = {2024-09-16},

booktitle = {15th annual International Micro Air Vehicle Conference and Competition},

pages = {301–308},

address = {Bristol, United Kingdom},

note = {Paper no. IMAV2024-36},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{imav2024-27:m_haffer_et_al,

title = {Extended Reception Coverage and Spoofing Localization of Direct Remote ID utilizing Ad-Hoc Mesh Networking},

author = {Mads Fogh Høffer and Victor Dahl Herlev and Guy Maalouf and Jes Jepsen and Erik Winkler and Ivan Panov and Kjeld Jensen},

editor = {T. Richardson},

url = {http://www.imavs.org/papers/2024/27.pdf},

year  = {2024},

date = {2024-09-16},

booktitle = {15$^th$ annual International Micro Air Vehicle Conference and Competition},

pages = {228–235},

address = {Bristol, United Kingdom},

note = {Paper no. IMAV2024-27},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{afridi2024unveiling,

title = {Unveiling the Impact of Drone Noise on Wildlife: A Crucial Research Imperative},

author = {Saadia Afridi and Kasper Hlebowicz and Dylan Cawthorne and Ulrik Pagh Schultz Lundquist},

year  = {2024},

date = {2024-01-01},

booktitle = {International Conference on Unmanned Aircraft Systems (ICUAS) 2024},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{rolland2024autonomous,

title = {Autonomous UAV volcanic plume sampling based on machine vision and path planning},

author = {Edouard GA Rolland and Kasper AR Grøntved and Anders Lyhne Christensen and Matthew Watson and Tom Richardson},

url = {https://findresearcher.sdu.dk/ws/portalfiles/portal/268877297/ICUAS_Preprint.pdf},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 International Conference on Unmanned Aircraft Systems (ICUAS)},

pages = {1064–1071},

organization = {IEEE},

abstract = {Drones currently serve as a valuable tool for in-situ sampling of volcanic plumes, but they still involve manual piloting. In this paper, we enable autonomous dual plume sampling by using a machine vision model to detect eruptions. When an eruption is detected, a sampling trajectory is automatically enerated to intercept the plume twice to collect comparative samples. The machine vision model is developed by training a YOLOv8 object detection model thanks to a database of 1505 images that feature labelled plumes. The obtained average precision value of the model’s plume class, at 90.7%, is comparable to that of state-of-the-art models for wildfire smoke monitoring. The performance of this method is assessed using a software-in-the-loop simulation of the drone and a simulated plume model. Although the results confirm the efficacy of using a machine vision model for triggering an onboard path-planning algorithm, it also suggests the potential for a hybrid strategy that integrates visual servoing with our proposed path-planning approach. },

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{maalouf2024airspace,

title = {Airspace Situational Awareness: Proposed Airspace Safety Concepts & State-of-the-Art Review of UAS Aircraft Detection Technologies},

author = {Guy Maalouf and Jes Hundevadt Jepsen and Kjeld Jensen},

url = {https://portal.findresearcher.sdu.dk/files/266012358/Airspace_Situational_Awareness_Proposed_Airspace_Safety_Concepts_State-of-the-art_Review_of_UAS_Aircraft_Detection_Technologies.pdf)},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 International Conference on Unmanned Aircraft Systems (ICUAS)},

pages = {1393–1400},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}