Machine Learning Algorithms for Service Robotics Applications in Precision Agriculture
Candidate: Angelo Tartaglia
Supervisor: Prof. Marcello Chiaberge
Date: October 2018
World population is growing faster than expected. Every year Earth resources are consumed faster, as proven by the early fall of the Earth Overshoot Day that claims the end of year resources. One of the simplest solutions to this problem would be investing in technologies and innovations towards a smart extraction of what population needs. In the last few years a lot of companies introduced automation and robots to improve production in terms of time and obviously cost. Agricultural world is not distant from this evolution; in fact many of the works attempted are now helped by a set of machines that simpliﬁes human work. Hitherto the application in precision agriculture has been always under the human control; there are a lot of applications that see the participation of a worker and in parallel a machine used for a lot of tasks. In the future may an entire ﬁeld will be managed by a group of automated robots that work together. Those machines will require a lot of speciﬁc features likes autonomous navigation, mapping, visual object recognition and many others. This thesis is part of that project and it regards the detection andclassiﬁcationoffruitsforfutureapplicationofauto-harvestingandhealthcontrol. Inamorespeciﬁcway apples will be considered in this thesis work for fruit application and methods and algorithms as Y.O.L.O. and Mask R-CNN to do the processing of images will be described.These techniques permits the detection of apples in post processing and in real-time with accuracies that range over 32% to 78%. The ﬁnal result can be used in future applications for spatial localization of fruits and for the detection of possible diseases. It should be emphasised that, even if the thesis shows the results of the object class apple, the algorithms can be applied in a wide range of objects with the only requirement of a diﬀerent training images dataset.