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Identifier 000441649
Title Optimization of recyclable materials collection on conveyor belts
Alternative Title Βελτιστοποίηση της συλλογής ανακυκλώσιμων υλικών από ιμάντες
Author Αγιομαυρίτη Αικατερίνη- Άρτεμις
Thesis advisor Τραχανιάς, Παναγιώτης
Reviewer Αργυρός, Αντώνιος
Τσακίρης, Δημήτριος
Abstract With the need for recycling of used materials growing steadily in order to save valuable resources of our planet, and given also that the rate at which recyclable materials reach the recycling factories and consequently the flow at which they fall on the conveyor belts in order to separate them is particularly large, the need for more efficient ways of separating and collecting these materials becomes apparent. In real life industrial set-ups, a large percentage of objects pass through the conveyor belts without being collected, at least not immediately. In addition, the main concern of a recycling factory is profit. Based on the above, the main focus of the present work is the optimization of the collection of the materials via the use of a robotic arm. The named optimization is based on the capabilities of the employed robotic arm and also on the market value of recyclable materials. Our approach is separated into two interrelated parts, the prediction of the material of the objects we expect to pass through the belt and their collection. In the first part, the materials are classified into three classes (paper, plastic and aluminum) using only information from previous throws on the belt and the characteristics of the materials (color and size). For this part, we employ Hidden Markov Models that are capable of accomplishing the required prediction. In the second part, a Path Planner is implemented targeting the optimization of the materials’ collection in terms of their cost. This is implemented via a Reinforcement Learning algorithm, specifically a Q-learning algorithm. Using a reward function the algorithm decides which is the next material to be collected. Finally, our approach is evaluated via simulated and real results, and its performance is also compared with that of a Proximity (Random) picker.
Language English
Issue date 2021-07-30
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/2/0/3/metadata-dlib-1628161393-60804-17039.tkl Bookmark and Share
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