New Artificial Intelligence approaches for future UAV Ground Control Stations

Ramírez-Atencia, Cristian; Rodríguez-Fernández, Víctor; González-Pardo, Antonio; Camacho, David

doi:10.1109/cec.2017.7969645

Cited by 13 publications

(7 citation statements)

References 23 publications

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“…The vast quantity of data that are gathered from UAV surveys opens up the opportunity for intelligent learning algorithms to speed up data processing as well as acquisition. AI has primarily been used in remote sensing to classify surface features (Kraaijenbrink et al, 2016), but embedding AI within UAV systems has streamlined data processing in other disciplines (Gonzalez et al, 2016;Ramirez-Atencia et al, 2017;Vasuki et al, 2014;Xu et al, 2018).…”

Section: Supraglacial Ponds and Ice Cliffsmentioning

confidence: 99%

Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

Taylor

Quincey

Smith

et al. 2021

Progress in Physical Geography: Earth and Environment

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Remote sensing technologies are integral to monitoring the mountain cryosphere in a warming world. Satellite missions and field-based platforms have transformed understanding of the processes driving changes in mountain glacier dynamics, snow cover, lake evolution, and the associated emergence of hazards (e.g. avalanches, floods, landslides). Sensors and platforms are becoming more bespoke, with innovation being driven by the commercial sector, and image repositories are more frequently open access, leading to the democratisation of data analysis and interpretation. Cloud computing, artificial intelligence, and machine learning are rapidly transforming our ability to handle this exponential increase in data. This review therefore provides a timely opportunity to synthesise current capabilities in remote sensing of the mountain cryosphere. Scientific and commercial applications were critically examined, recognising the technologies that have most advanced the discipline. Low-cost sensors can also be deployed in the field, using microprocessors and telecommunications equipment to connect mountain glaciers to stakeholders for real-time monitoring. The potential for novel automated pipelines that can process vast volumes of data is also discussed, from reimagining historical aerial imagery to produce elevation models, to automatically delineating glacier boundaries. Finally, the applications of these emerging techniques that will benefit scientific research avenues and real-world societal programmes are discussed.

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Section: Supraglacial Ponds and Ice Cliffsmentioning

confidence: 99%

Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

Taylor

Quincey

Smith

et al. 2021

Progress in Physical Geography: Earth and Environment

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“…Many articles on mission planning opt for the use of AI to achieve improvement in one or more aspects of observation missions. For example, [55] analyses how AI can be used to reduce operator load on the ground during UAV missions. This section will provide a technical background on some AI topics used in mission planning.…”

Section: Artificial Intelligencementioning

confidence: 99%

Multi-Objective Heterogeneous Multi-Asset Collection Scheduling Optimization with High-Level Information Fusion

Kande

Abielmona

Harb

et al. 2021

2021 IEEE International Systems Conference (SysCon)

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Surveillance of areas of interest through image acquisition is becoming increasingly essential for intelligence services. Several types of platforms equipped with sensors are used to collect good quality images of the areas to be monitored. The evolution of this field has different levels: some studies are only based on improving the quality of the images acquired through sensors, others on the efficiency of platforms such as satellites, aircraft and vessels which

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“…The problem is modeled as a constraint satisfaction problem and solved using multi-objective GA. This work has been further extended by (Ramirez-Atencia et al, 2017b) to utilize re-planning and analysis of operator training in the control center. For a similar problem of a mission planning for cooperative UAV teams, a solution was proposed by (Bello-Orgaz et al, 2016) that uses GA to optimize a weighted linear combination of mission's makespan and fuel consumption.…”

Section: Related Workmentioning

confidence: 99%

Extended Colored Traveling Salesperson for Modeling Multi-Agent Mission Planning Problems

Miloradović

Çürüklü

Ekström

et al. 2019

Proceedings of the 8th International Conference on Operations Research and Enterprise Systems

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In recent years, multi-agent systems have been widely used in different missions, ranging from underwater to airborne. A mission typically involves a large number of agents and tasks, making it very hard for the human operator to create a good plan. A search for an optimal plan may take too long, and it is hard to make a time estimate of when the planner will finish. A Genetic algorithm based planner is proposed in order to overcome this issue. The contribution of this paper is threefold. First, an Integer Linear Programming (ILP) formulation of a novel Extensive Colored Traveling Salesperson Problem (ECTSP) is given. Second, a new objective function suitable for multi-agent mission planning problems is proposed. Finally, a reparation algorithm to allow usage of common variation operators for ECTSP has been developed.

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New Artificial Intelligence approaches for future UAV Ground Control Stations

Cited by 13 publications

References 23 publications

Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

Multi-Objective Heterogeneous Multi-Asset Collection Scheduling Optimization with High-Level Information Fusion

Extended Colored Traveling Salesperson for Modeling Multi-Agent Mission Planning Problems

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