An unmanned ground vehicle (UGV) is a vehicle that operates while in contact with the ground and without an onboard human presence. UGVs can be used for many applications where it may be inconvenient, dangerous, or impossible to have a human operator present. Generally, the vehicle will have a set of sensors to observe the environment, and will either autonomously make decisions about its behavior or pass the information to a human operator at a different location who will control the vehicle through teleoperation.
The UGV is the land-based counterpart to unmanned aerial vehicles and unmanned underwater vehicles. Unmanned robotics are being actively developed for both civilian and military use to perform a variety of dull, dirty, and dangerous activities.
In 1904, the Spanish engineer Leonardo Torres Quevedo, while developing a radio-based control system he named Telekino, chose to conduct an initial test in the form of a three-wheeled land vehicle (tricycle), which had an effective range of just 20 to 30 meters, in which appears to be the first known example of a radio-controlled unmanned ground vehicle.
A working remote controlled car was reported in the October 1921 issue of RCA's World Wide Wireless magazine. The unmanned car was controlled wirelessly via radio; it was thought the technology could someday be adapted to tanks. In the 1930s, the USSR developed the Teletank, a small tank, armed with a machine gun, and remotely controlled by radio from another tank. Teletanks operated in the Winter War (1939–1940) against Finland and at the start of the German-Soviet War after the Axis powers invaded the USSR in 1941. During World War II, the British developed a radio-controlled version of their Matilda II infantry tank in 1941. Known as "Black Prince", it would have been used for drawing the fire of concealed anti-tank guns, or for demolition missions. Due to the costs of converting the transmission system of the tank to Wilson-type gearboxes, an order for 60 tanks was cancelled.
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Deep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects,
thumb|Un THeMIS, robot militaire de fabrication estonienne. Un robot militaire, aussi appelé arme autonome, est un robot, autonome ou contrôlé à distance, conçu pour des applications militaires. Les drones sont une sous-classe des robots militaires. Des systèmes sont déjà actuellement en service dans un certain nombre de forces armées, où ils s'avèrent efficaces. Le drone "Predator", par exemple, est capable de prendre des photographies de surveillance, et même à lancer des missiles air-sol AGM-114N "Hellfire" II ou des GBU-12 "Paveway" II dans le cas du MQ-1 et du MQ-9.
vignette|exemple de robot autonome de type rover Un robot autonome, également appelé simplement autorobot ou autobot, est un robot qui exécute des comportements ou des tâches avec un degré élevé d'autonomie (sans influence extérieure). La robotique autonome est généralement considérée comme un sous-domaine de l'intelligence artificielle, de la robotique et de l'. Les premières versions ont été proposées et démontrées par l'auteur/inventeur David L. Heiserman.
Explore la prévision des trajectoires dans les véhicules autonomes, en mettant l'accent sur les modèles d'apprentissage profond pour prédire les trajectoires humaines dans les scénarios de transport socialement conscients.
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Explore les modèles prédictifs et les traceurs pour les véhicules autonomes, couvrant la détection d'objets, les défis de suivi, le suivi en réseau neuronal et la localisation des piétons en 3D.
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