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Mostrati risultati da 178 a 197 di 318
Tipologia Anno Titolo Titolo inglese Autore File
Lauree magistrali 2024 Innovative Solutions for Policy Optimisation of Model-Based Reinforcement Learning Algorithms Innovative Solutions for Policy Optimisation of Model-Based Reinforcement Learning Algorithms CALÌ, MARCO
Lauree magistrali 2022 Integrating State-of-the-Art Approaches for Anomaly Detection and Localization in the Continual Learning Setting Integrating State-of-the-Art Approaches for Anomaly Detection and Localization in the Continual Learning Setting BUGARIC, JOVANA
Lauree magistrali 2024 Integration of Machine Learning Algorithms and Simscape Modeling for Fault Detection, Diagnosis, and Evaluation in Heat Pump Systems Integration of Machine Learning Algorithms and Simscape Modeling for Fault Detection, Diagnosis, and Evaluation in Heat Pump Systems DE MARCHI, FRANCESCO
Lauree magistrali 2022 Integrazione tra automazione e manutenzione nel World Class Manufacturing: il caso Tetra Pak Integration between automation and maintenance in World Class Manufacturing: the Tetra Pak case COLOMBO, ALDO
Lauree magistrali 2024 Intelligent Path Planning and Control for Autonomous Underwater Exploration Intelligent Path Planning and Control for Autonomous Underwater Exploration VERONESE, DELIA
Lauree magistrali 2025 Interaction Control for Collaborative Robots: An Adaptive Impedance-Based Approach in Contact-Rich and Uncertain Scenarios Interaction Control for Collaborative Robots: An Adaptive Impedance-Based Approach in Contact-Rich and Uncertain Scenarios GIZZARONE, MANUEL
Lauree magistrali 2024 Interfacing ns-3 and ROS2 for Edge-Controlled Robotic Systems: Impact of Network Dynamics on Performance Interfacing ns-3 and ROS2 for Edge-Controlled Robotic Systems: Impact of Network Dynamics on Performance EBRAHIMI, MAEDEH
Lauree magistrali 2022 Interpretable Anomaly Detection for Automated Filling Systems through Machine Learning approaches Interpretable Anomaly Detection for Automated Filling Systems through Machine Learning approaches BELLAN, RICCARDO
Lauree magistrali 2023 Iterative Learning Control analysis for automotive testbed applications Iterative Learning Control analysis for automotive testbed applications MUSTACCHI, MARCO
Lauree magistrali 2022 Joint torques estimation of a robotic arm using neural networks Joint torques estimation of a robotic arm using neural networks D'ADDATO, GIULIA
Lauree magistrali 2021 Kalman filtering for temperature estimation of electric motors Kalman filtering for temperature estimation of electric motors SÁNCHEZ EL RYFAIE, SAMIRA CAROLINA
Lauree magistrali 2024 Kinodynamic RRT* for path planning of a small fixed-wing UAV Kinodynamic RRT* for path planning of a small fixed-wing UAV LACOVARA, STEFANO
Lauree magistrali 2025 KNNIFE: a data-informed Feature Importance for Isolation Forest and its extensions KNNIFE: a data-informed Feature Importance for Isolation Forest and its extensions DE VIDI, RICCARDO
Lauree magistrali 2022 Latent Replay for Continual Learning on Edge devices with Efficient Architectures Latent Replay for Continual Learning on Edge devices with Efficient Architectures TREMONTI, MATTEO
Lauree magistrali 2024 Learning Simultaneously Policies and Action Sequences for Robotic Manipulation Tasks Learning Simultaneously Policies and Action Sequences for Robotic Manipulation Tasks In this research, aim is to explore how robots can learn to perform complex tasks more effectively by combining reinforcement learning, behavior trees, and genetic programming. The idea is to help robots simultaneously figure out not just what actions to take, but also the best sequence of those actions to complete tasks like grasping or assembling objects. By using reinforcement learning, the robot can learn from trial and error, improving its decision-making over time. Behavior trees offer a structured way to define and adapt complex behaviors, making the robot's actions more flexible. Meanwhile, genetic programming will be used to evolve and optimize these behaviors, helping the robot find the most efficient strategies even in unpredictable environments. Ultimately, this research aims to create robots that are not only more capable but also more adaptable to the challenges they encounter in the real world. KURTOGLU, METEHAN
Lauree magistrali 2023 Learning stack of tasks for robotic mobile manipulation Learning stack of tasks for robotic mobile manipulation ADAMI, ALESSANDRO
Lauree magistrali 2025 Learning-based Energy Control of Underactuated Robots Learning-based Energy Control of Underactuated Robots FATTAHI, AMIRHOSSEIN
Lauree magistrali 2023 Learning-based Model Predictive Controller for Lateral Control of Autonomous Vehicles Learning-based Model Predictive Controller for Lateral Control of Autonomous Vehicles LORENZI, CRISTIAN
Lauree magistrali 2021 Learning-based Nonlinear Model Predictive Control for A Motorcycle Virtual Rider Learning-based Nonlinear Model Predictive Control for A Motorcycle Virtual Rider BIANCHIN, FRANCESCO
Lauree magistrali 2023 Learning-based Nonlinear Model Predictive Control with application to quadrotor control Learning-based Nonlinear Model Predictive Control with application to quadrotor control COLAVITTI, GIACOMO
Mostrati risultati da 178 a 197 di 318
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