Unmanned vehicles

Illustration Photo: Agricultural drone remote controlled by an operator (CC0 Creative Commons from Pixabay.com)

Figure: UAV used for the inventory and traceability system (credits: Tiago M. Fernández-Caramés, Oscar Blanco-Novoa, Iván Froiz-Míguez and Paula Fraga-Lamas)

Illustration Photo: Border Surveillance Drone operated by U.S. Customs Border Patrol (credits: Jonathan Cutrer / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Photo: UAV equipped with multispectral sensor, GPS device and digital camera. (credits: G Tanda and V. Chiarabini)

Photo d'illustration: Un drone de sauvetage conçu pour sauver des vies, développé par un start-up basée à l'ESA aux Pays-Bas. Inspirée par la crise des réfugiés, la société Avy travaille sur des drones robustes et de longue durée capables de détecter les personnes en détresse et, si nécessaire, de larguer gilets de sauvetage, bouées de sauvetage, nourriture et médicaments. Copyright Jan-Willem Groen, www.fotografiegroen.nl

Photo: Qlex Creo © QLEX Creo

Illustration Photo: Drone flying over a crop field (credits: Greg Shine, BLM / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Illustration Photo: Drone flying over an airport (credits: Chris Osborne / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Photo: UAV platform and airborne imaging hyperspectral sensor. (A) UAV. (B) Hyperspectral sensor (Photograph credit: Xiangyu Ge).

Illustration Photo: Israeli Made Guardium UGV (credits: Cpl. Zev Marmorstein, IDF Spokesperson's Unit / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Illustration Photo: Drone DJI Phantom 3 (credits: Julien Sabardu / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Photo d'illustration: Les ingénieurs de Sandia ont conçu le robot de sauvetage dans les mines Gemini-Scout pour identifier les dangers et venir en aide aux mineurs piégés. Le robot est capable de naviguer dans 18 pouces d’eau, de ramper sur des rochers et des tas de gravats, et de passer devant les sauveteurs pour évaluer les environnements précaires et aider à la planification des opérations (crédits: Randy Montoya / Sandia Labs / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Photo d'illustration: Le micro robot terrestre tactique est un système léger qui permet aux équipes de destruction d’ordonnances explosives et autres unités tactiques d’explorer des zones d’intérêt et d’examiner les dispositifs suspects avant l’envoi de personnel. (crédits: U.S. Air Force photo/Staff Sgt. Andrew Lee / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Illustration Photo: Watchkeeper Air Vehicle 20 (credits: Think Defence / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Illustration Photo: Pesticide Spraying UAV (CC0 Creative Commons from Pixabay.com)

Photo: Results of the detection of damaged tree categories on test area D. C1, C2, C3 and C4 indicate the estimated class by our CNN classification model together with the corresponding probability. The symbols “+” and “−” indicate respectively correct and incorrect class estimation by our model. (credits: Anastasiia Safonova, Siham Tabik, Domingo Alcaraz-Segura, Alexey Rubtsov, Yuriy Maglinets and Francisco Herrera)

Photo: WasteSharks à Dubaï, Émirats Arabes Unis (© RanMarine Technology BV https://www.ranmarine.io)

Food Security,Precision Farming,Internet of Things

Illustration Photo: Drone Delivery (credits: www.routexl.com / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Photo d'illustration: Le pont Bukhang à Busan en Corée du Sud (crédits: Jens-Olaf Walter / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Photo: Proposed communications architecture (credits: Tiago M. Fernández-Caramés, Oscar Blanco-Novoa, Manuel Suárez-Albela and Paula Fraga-Lamas)

Photo d'illustration: Les producteurs de blé Noah Williams (à gauche) et Garrett Duyck, spécialiste de la conservation des sols au Service de la conservation des ressources naturelles, suivent les données des capteurs de sol installés sur un champ de blé couvert et un champ de blé en jachère. Les données aideront Williams à élaborer un plan de culture de couverture qui maximise l’humidité du sol. (crédits: NRCS Oregon / Flickr Creative Commons Attribution-NoDerivs 2.0 Generic (CC BY-ND 2.0))

Photo: Driverless vehicles are combined with delivery robots to deploy packages all the way to the consumer. © Continental AG

Illustration Photo: Agricultural drone (CC0 Creative Commons from Pixabay.com)

Illustration Photo: California Citrus (credits: Jasperdo / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Photo: The Intel Falcon 8+ drone conducts a visual inspection of the historic Stone Arch Bridge in Minneapolis. Working with the Minnesota Department of Transportation and Collins Engineers, Intel used its commercial drone technology to help automate and expedite inspection of the pedestrian and bicycle bridge. (Credit: Intel Corporation)

Illustration Photo: Multiple-Rotor Remote Sensing Aerial Copter (credits: University of Arkansas Division of Agriculture photo by Mary Hightower / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Picture: Proposed UAV IoT architecture. (credits: Thomas Lagkas, Vasileios Argyriou, Stamatia Bibi and Panagiotis Sarigiannidis)

Photo: Hycopter, long endurance hydrogen-electric drone (credit: HES Energy Systems)

Picture: Mobile crowdsensing (credits: Milan Erdelj, Borey Uk, David Konam and Enrico Natalizio)

Photo: Mike Gore, Ph.D. '09, and his lab conduct research using remote sensing technology to explore the genetic basis of trait variation in crops such as corn, oat and cassava. The research leads to more efficient and effective selection of plant variations for the high-yielding, or highly nutritious, cultivar that can help feed the world's population. Gore is also part of the leadership in recently formed CIDA Cornell Initiative for Digital Agriculture, which is leveraging digital innovations in agriculture to improve the sustainability, profitability, resiliency and efficiency of the world's food systems. Credit: Lindsay France, Cornell University

Photo d'illustration: Système sans pilote Desert Hawk (crédits: Think Defence / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Photo: U.S. Army pilot Lt. Col. Carl Ott controls an S-76B helicopter via tablet, as it hovers above a field in Fort Eustis, Virginia (credit: DARPA)

Illustration Photo: Aerial footage of palm oil and the forest in Sentabai Village, West Kalimantan, Indonesia (credits: Nanang Sujana / CIFOR / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Illustration: Rolls-Royce’s Intelligent Awareness System (IA) uses AI-powered sensor fusion and decision-making by processing data from lidar, radar, thermal cameras, HD cameras, satellite data and weather forecasts (credit: Rolls-Royce)

Illustration Photo: Australian Forest (Public Domain from Pixabay.com)

Illustration Photo: Agricultural drone at Steve & Lizabeth Sigdestad Farm (credits: USDA NRCS South Dakota / Flickr Creative Commons Attribution-ShareAlike 2.0 Generic (CC BY-SA 2.0))

Illustration Photo: Drone over York River (credits: D. Gong / VIMS / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Illustration Photo: Rice field (Public Domain from Pixabay.com)

Illustration Photo: 3DR Solo drone (credits: USGS Unmanned Aircraft Systems / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Illustration Photo: Coast Guard Research and Development Center personnel test an unmanned maritime system from the Coast Guard Cutter Healy in the Arctic, July 29, 2017. (credits: U.S. Coast Guard photo by Petty Officer 2nd Class Meredith Manning / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Figure: Data acquisition diagram.

Illustration of a drone flies along a coastline to collect data from deployed sensors. By mainstream open-source or commercial flight controllers, a flight path consists of a sequence of way-points that the drone visits and makes turn at, so they are also called turning points (red solid points). More turning points means more energy consumption of the drone since more flight time and distance to cover, however, it also means closer the drone can fly to sensors to collect data. Fewer turning points consumes less drone energy, but cost sensors to use higher power to transmit data due to the longer distance. The best trade-off with limited drone and sensors energy must be found. (credits: Runqun Xiong and Feng Shan)

Illustration Photo: Agricultural drone (CC0 Creative Commons from Pixabay.com)

Figure: Software developed to monitor all the information in real time. (credits: Alberto Rivas, Pablo Chamoso, Alfonso González-Briones and Juan Manuel Corchado)

Photo: Le robot Quad-Morphing (© Valentin Rivière et Stéphane Viollet, Institut des sciences du mouvement – Étienne Jules Marey (CNRS/Aix-Marseille Université).)

Photo: iBubble Team (credit: Notilo Plus)

Photo: The overall air-ground multi-sensor monitoring system (credits: Yawei Zhang, Du Chen, Shumao Wang, Lei Tian)

Illustration Photo: Sorghum field (credits: Harry Rose / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

Illustration Photo: Agricultural drone (CC0 Creative Commons from Pixabay.com)

Illustration Photo: Agricultural drone (CC0 Creative Commons from Pixabay.com)

Photo: One of the high-tech drones at work in a vineyard (credit: QUT)

Photo: Le drone Uavia survolant une centrale électrique (crédit: Uavia)

Photo: Xcel Energy, a leader in using drone technology to inspect energy infrastructure, will be the first utility in the nation to routinely fly unmanned aircraft beyond the operator's line of sight when it begins surveying transmission lines near Denver, Colorado. (Photo: Northern Plains UAS Test Site)

Photo: SwarmDiver(TM) (credit: Aquabotix)

Pictorial Representation of UAV based Fishing Technique (credits: T. Ahilan; V. Aswin Adityan; S. Kailash)

Photo: Detection of weeds between and within crop rows using UAV Imagery (credits: Ana I. de Castro, Jorge Torres-Sánchez, Jose M. Peña, Francisco M. Jiménez-Brenes, Ovidiu Csillik and Francisca López-Granados)

Photo: Unmanned aerial vehicle Geoscan 201 launching and landing (credits: Sergey V. Cherkasov, Anvar M. Farkhutdinov, Dmitriy P. Rykovanov, Arbi A. Shaipov)

Illustration Photo: Yara Birkeland autonomous ship under way, Kongsberg Maritime/Yara (credits: Ørnulf Rødseth / Flickr Creative Commons Attribution-NoDerivs 2.0 Generic (CC BY-ND 2.0))

Photo: AutoNaut's Autonomous Boat propelled by Waves. Copyright AutoNaut

Photo: DEEP AERO UTM technology platform is the first AI driven, autonomous system to manage drone traffic. (credit: DEEP AERO)

Photo: On-board direction RF receiver (left) and RF transmitter on the ground (credit: Korea Advanced Institute of Science and Technology (KAIST))

Illustration Photo: Pesticide spraying by drone (CC0 Creative Commons from Pixabay.com)

Danielle Bryant, right, an oceanographer from the Naval Oceanographic Office, establishes a satellite connection to the Glider Operations Center at NAVOCEANO before launching the seaglider unmanned underwater vessel from the Military Sealift Command oceanographic survey ship USNS Henson. The vessel is designed to collect physical oceanography data in deep water. Henson is underway off the coast of Fortaleza, Brazil for Oceanographic-Southern Partnership Station 2010 conducting survey demonstrations with the Brazilian Directorate of Hydrograph and Navigation. Oceanographic-Southern Partnership Station is an oceanographic surveying and information exchange program between subject matter experts with partner nations in the U.S. Southern Command area of responsibility.

Illustration Photo: Unmanned Aerial Vehicle (CC0 Creative Commons from Pixabay.com)

Illustration Photo: The senseFly eBee flies over the Duke University Marine Lab. (credits: Duke Marine Robotics and Remote Sensing Lab / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

Illustration Photo: Drone flying over a city (CC0 Creative Commons from Pixabay.com)

Illustration Photo: Agricultural Drone (CC0 Creative Commons from Pixabay.com)

Photo: Custom-made two-axis gimbal hosting the hyperspectral camera (SolidWorks 3D model). (credits: Fernando Vanegas, Dmitry Bratanov, Kevin Powell, John Weiss and Felipe Gonzalez)

Illustration Photo: Vineyard (CC0 Creative Commons from Pixabay.com)

Photo: Print screen from video "Future of autonomous air travel: Boeing unveils new cargo air vehicle prototype" (credit: Boeing)

Picture: Obstruction phase (credits: Keisuke Watanabe, Kyoko Takashima, Kazuho Mitsumura, Koshi Utsunomiya, Shiyun Takasaki)

Photo of the UAS (credits: Enrique Moguel, José M. Conejero, Fernando Sánchez-Figueroa, Juan Hernández, Juan C. Preciado, Fernando Sánchez-Figueroa and Roberto Rodríguez-Echeverría)

Photo: Leti's 360Fusion Anti-Crash System Embedded in a Drone (credit: Leti)

Photo: Scout TM (credit: American Robotics)

Illustration Photo: Drone flying over a crop field (CC0 Creative Commons from Pixabay.com)

Malcolm Connolly (left) and Chris Fleming of Cyberhawk, an aerial inspection and surveying company, use an Intel Falcon 8+ system during the inspection of an operating gas terminal in St Fergus, Scotland. Unmanned aerial vehicle systems reduce employee risk, increase speed and accuracy, and save money that would be lost during a potential production closure. (Credit: Intel Corporation)

Photo: Passenger Drone's Two-Seater Electric Manned Aircraft (credit: Passenger Drone)

Illustration Photo: Drone used for bridge inspections (credits: Oregon Department of Transportation / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Illustration Photo: Freight for air cargo (Public Domain from Pixabay.com)

Illustration Photo: Multi-rotors drone (Public Domain from Pixabay.com)

Photo: Parrot Bluegrass (credit: Parrot)

Photo: System structure (credits: Authors: Yaowei Long, Hong Sun, Minzan Li, Wei Yang, Haojie Liu, Zichun Sun, Xu Wang)

Photo: Autopilot from a drone for the navigation system (credit: Hands Free Hectare)

Illustration Photo: Drone Spraying (Public Domain from Pixabay.com)

Photo: DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) program envisions future small-unit infantry forces using small unmanned aircraft systems (UASs) and/or small unmanned ground systems (UGSs) in swarms of 250 robots or more to accomplish diverse missions in complex urban environments. By leveraging and combining emerging technologies in swarm autonomy and human-swarm teaming, the program seeks to enable rapid development and deployment of breakthrough capabilities to the field. DARPA is continuing its pursuit of these goals through awarding Phase 1 contracts to teams led by Raytheon BBN Technologies (Cambridge, Massachusetts) and the Northrop Grumman Corporation (Linthicum, Maryland). Credit: DARPA.

Photo: Print screen from the video "HiRO DRONE: Innovative Response to Critical Injury" (credit: Hiro Saves)

Photo: A Flirtey drone delivers an Automated External Defibrillator (AED) to assist a victim of cardiac arrest (credit: REMSA)

Illustration Photo: Maize field (Public Domain from Pixabay.com)

Photo: Delair UX11 (credit: Delair)

Illustration Photo: drone (Public Domain from Pixabay.com)

Photo: The PLANET approach for large-scale cooperation of highly heterogeneous networked systems (credits: Capitán Fernández Jesús, Martínez de Dios José Ramiro, Maza Alcañiz Iván, Fabresse Felipe Ramón, Ollero Baturone Aníbal)

Illustration Photo: Drone inspecting a building (Public Domain from Pixabay.com)

Photo: DARPA’s SideArm research effort seeks to create a self-contained, portable apparatus able to horizontally launch and retrieve unmanned aerial systems (UASs) of up to 900 pounds. Aurora Flight Sciences recently tested a full-scale SideArm technology demonstration system that repeatedly captured a Lockheed Martin Fury UAS accelerated to representative flight speeds via an external catapult. (credit: DARPA)

Illustration Photo: Organ Human transport by drone (credits: Lars Plougmann / Flickr Creative Attribution-ShareAlike 2.0 Generic (CC BY-SA 2.0))

Illustration Photo: DJI Phantom 4 drone (credits: Andri Koolme / Flickr Creative Attribution 2.0 Generic (CC BY 2.0))

Photo: The Mark II, from Heurobotics at Embry-Riddle Aeronautical University (credit: Heurobotics)

Illustration Photo: DJI Mavic Pro (credits: Leigh Miller | www.leighmiller.ca / Flickr Creative Commons Attribution-ShareAlike 2.0 Generic (CC BY-SA 2.0))

Picture: System for extending internet access via fast deployable portable routers (credit: Reynolds Karl)

Illustration Photo: DJI Phantom 3 (credits: Lee / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))