Riccardo Tesse
A Deep Learning approach to Instance Segmentation of indoor environment.
Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
Nowadays, mobile robots are frequently used in both indoor and outdoor situations, including agriculture, transportation in industries, surveillance, and cleaning buildings. These are being developed for several applications where long-term capabilities would be advantageous. The primary goal of mobile robotics is to build fully autonomous machines, meaning that they must be able to carry out their jobs without assistance from humans. Their industrial and technical use is continuously becoming more significant, especially when reliability (the uninterrupted and dependable completion of tasks like surveillance), accessibility (the inspection of locations that are inaccessible to humans, such as confined spaces, hazardous environments, or remote sites), or cost are considered.
Computer vision is playing a vital part in making these projects more efficient due to the enormous strides that Machine Learning and Deep Learning have achieved in the sector
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