Interactions between coastal waters and marine-terminating glaciers in the Polar Regions play a significant role in global sea level rise fueled by a rapidly warming Arctic. The risk of glacier calving, and the abundance of ice, can make it impossible for surface vessels to access the waters near glacier termini. Alternative methods using manned aircraft are expensive. As a result, oceanographic measurements are limited near glacier termini. We present an uncrewed aerial vehicle (UAV) with an on-board winch system that allows oceanographic profiling in remote, hazardous areas using a commercial conductivity, temperature, and depth (CTD) sensor payload. The UAV is optimized for easy handling and deployment and is capable of high-speed and efficient cruise flight. An autopilot system provides pilot assistance and autonomous flight capabilities. The total weight of the UAV including payload is 6.5 kg with an endurance of 24 min. Testing of the system was conducted in South Greenland during winter conditions in March 2023 with successful profiles collected near a glacier terminus (<5 m) and in small openings in ice mélange (2.2 m). The system proved capable, reliable, and efficient. Further development of the system will allow other sensors for an even more flexible measurement suite.
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http://dx.doi.org/10.1016/j.ohx.2024.e00518 | DOI Listing |
Proc Hum Factors Ergon Soc Annu Meet
September 2024
NASA Langley Research Center, Hampton, VA, USA.
Uncrewed Aerial Systems (UAS) show promise in urban air transport, package delivery, and emergency services. UAS efficiency can be significantly improved by having multiple operators () managing a greater number of vehicles (), or the architecture of operation. The current study investigates how workload affects operators' task-allocation decision-making and the potential mediating effects of two crucial human factors, trust and self-confidence.
View Article and Find Full Text PDFFront Robot AI
December 2024
School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, United Kingdom.
This paper proposes a solution to the challenging task of autonomously landing Unmanned Aerial Vehicles (UAVs). An onboard computer vision module integrates the vision system with the ground control communication and video server connection. The vision platform performs feature extraction using the Speeded Up Robust Features (SURF), followed by fast Structured Forests edge detection and then smoothing with a Kalman filter for accurate runway sidelines prediction.
View Article and Find Full Text PDFPeerJ Comput Sci
September 2024
Postgraduate Program in Electrical Engineering, Universidade Federal do Pará, Belém, Pará, Brazil.
The emergence of long-range (LoRa) technology, together with the expansion of uncrewed aerial vehicles (UAVs) use in civil applications have brought significant advances to the Internet of Things (IoT) field. In this way, these technologies are used together in different scenarios, especially when it is necessary to have connectivity in remote and difficult-to-access locations, providing coverage and monitoring of greater areas. In this sense, this article seeks to determine the best positioning for the LoRa gateway coupled to the drone and the optimal spreading factor (SF) for signal transmission in a LoRa network, aiming to improve the connected devices (SNR), considering a suburban and densely wooded environment.
View Article and Find Full Text PDFPLoS One
October 2024
Department of Ecology & Evolution, Stony Brook University, Stony Brook, New York, United States of America.
Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location.
View Article and Find Full Text PDFNature
October 2024
Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Aerial light detection and ranging (lidar) has emerged as a powerful technology for mapping urban archaeological landscapes, especially where dense vegetation obscures site visibility. More recently, uncrewed aerial vehicle/drone lidar scanning has markedly improved the resolution of three-dimensional point clouds, allowing for the detection of slight traces of structural features at centimetres of detail across large archaeological sites, a method particularly useful in areas such as mountains, where rapid deposition and erosion irregularly bury and expose archaeological remains. Here we present the results of uncrewed aerial vehicle-lidar surveys in Central Asia, conducted at two recently discovered archaeological sites in southeastern Uzbekistan: Tashbulak and Tugunbulak.
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