As the number of research activities and practical deployments of unmanned vehicles has shown a rapid growth, topics related to their communication with operator and external infrastructure became of high importance. As a result a trend of employing IP communication for this purpose is emerging and can be expected to bring significant advantages. However, its employment can be expected to be most effective using broadband communication technologies such as Wireless Local Area Networks (WLANs). To verify the effectiveness of such an approach in a specific case of surface unmanned vehicles, the paper includes an overview of IP-based MAVLink communication advantages and requirements, followed by a laboratory and field-experiment study of selected WLAN technologies, compared to popular narrowband communication solutions. The conclusions confirm the general applicability of IP/WLAN communication for surface unmanned vehicles, providing an overview of their advantages and pointing out deployment requirements.
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http://dx.doi.org/10.3390/s22020655 | DOI Listing |
Integr Environ Assess Manag
January 2025
Ionian Department, University of Bari Aldo Moro, Bari, Italy.
Fugitive or diffuse methane emissions constitute an important source of damage to the environment, much greater even than CO2 both over a time span of 20 years and over a longer time span of 100. It is therefore of preeminent importance to undertake all the efforts necessary to implement new tools, protocols, and methods that contribute to the identification and measurement of these emissions to implement site-specific actions of mitigation, repair, and conscious management of the emitting plants. Among the remote sensing and leak detection technologies currently used, the tunable diode laser absorption spectroscopy (TDLAS) method plays a relevant role.
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January 2025
Department of Basic Courses, Xi'an Research Institute of Hi-Tech, Xi'an, 710025, China.
Unmanned aerial vehicle (UAV) path planning is a constrained multi-objective optimization problem. With the increasing scale of UAV applications, finding an efficient and safe path in complex real-world environments is crucial. However, existing particle swarm optimization (PSO) algorithms struggle with these problems as they fail to consider UAV dynamics, resulting in many infeasible solutions and poor convergence to optimal solutions.
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January 2025
Centre for Automation and Robotics (CAR), Spanish National Research Council (CSIC), 28006, Madrid, Spain.
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Institute of Agricultural Sciences, Spanish National Research Council (ICA-CSIC), Serrano 115b, 28006 Madrid, Spain.
Identifying weed species at early-growth stages is critical for precision agriculture. Accurate classification at the species-level enables targeted control measures, significantly reducing pesticide use. This paper presents a dataset of RGB images captured with a Sony ILCE-6300L camera mounted on an unmanned aerial vehicle (UAV) flying at an altitude of 11 m above ground level.
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Instituto de Química, Universidade Federal de Goiás, 74690-900, Goiânia, GO, Brazil; Instituto Nacional de Ciência e Tecnologia de Bioanalítica, Campinas, 13084-971, SP, Brazil. Electronic address:
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