Riccardo Tassi
Design of a behavior-based navigation algorithm for autonomous tunnel inspection.
Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
The modern world is characterized by the presence of a significant amount of subterranean infrastructures, including networks of tunnels, caverns, and the urban underground. Each of these environments offers intricate settings that could create difficulties for exploration, inspection, and several other activities. Conditions might deteriorate and vary over time, and there may be various risks. Most of the time, this confluence of difficulties and dangers creates circumstances that are too dangerous for workers. Situations like gas leaks, explosions, rock falls, confinement, and prolonged exposure to dust are all potentially lethal. Robotic solutions are thus required to operate when and where human risk is too high.
Autonomous robots can lower risks by taking over potentially hazardous jobs for workers
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