Student Projects
Review the projects below and send an email to the project contact.
Learning, Predicting and Control Diffusion via Optimal Transport
The stochastic diffusion equations ruling the dynamics of particles at the micro- and nano- scale are captured by energy-minimizing dynamics when observed macroscopically, i.e., at a population level. This framework encompasses, for instance, single cells perturbation responses to chemical, genetic or mechanical stimuli, gene expression and cell differentiation. Recent advances in the theory of optimal transport and optimization in the Wasserstein space have created unprecedented opportunities to tackle these and other problems at scale. This active research area provides an excellent playground for exploring advanced mathematical concepts, deploying sophisticated learning and optimization algorithms, and solving open problems in biology, medicine, and various other fields. The project can be both theoretical and applied, and can include topics on optimization, optimal transport, deep learning, and biology. The project can be tailored to the preferences and experiences of the student.
Keywords
Diffusion, Optimal Transport, Optimal Control, Optimization, Biology
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Semester Project , Master Thesis
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Published since: 2024-04-09 , Earliest start: 2024-04-14 , Latest end: 2024-09-01
Organization Research D'Andrea
Hosts Terpin Antonio
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Chemistry
The Way of Water: Development of a fleet of water-based drones for live performance
This project focuses on developing autonomous robots for synchronized performances on water. Equipped with kinetic water fountains, RGB lighting, and ultrasonic mist generators, the robots are designed to execute planned choreographies. The system utilizes robotics control, wireless communication, and positioning technologies to coordinate movements, and payload activation, facilitating complex pattern generation and synchronization. The objective is to advance the application of distributed robotic systems in creating structured and cohesive visual displays on water.
Keywords
Water based rovers, Electronics development, Distributed Robotics, Control Systems, Game design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2024-03-26
Organization Research D'Andrea
Hosts Ramachandran Aswin
Topics Arts , Information, Computing and Communication Sciences , Engineering and Technology
Teaching a robot to master a board game using Reinforcement Learning
The master thesis aims to create a physics-based simulation with Brax or MuJoCo for a robot to learn board game strategies via reinforcement learning. Utilizing a pre-built 2x 2D gantry robot integrated with ROS2, the project seeks to train the robot to learn the game from scratch and improve its play against both human and robotic opponents. The primary goal is rapid learning and superior performance, with a focus on understanding the factors of victory in games like this between robots trained on the same algorithm. All this will be performed in simulation and on a real robot.
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Semester Project , Master Thesis
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Published since: 2024-03-15
Organization Research D'Andrea
Hosts Ramachandran Aswin
Topics Engineering and Technology
CyberRunner: Pushing the Boundary of Autonomy
CyberRunner is an AI robot whose task is to learn how to play the popular and widely accessible labyrinth marble game. The labyrinth is a game of physical skill whose goal is to steer a marble from a given start point to the end point. In doing so, the player must prevent the ball from falling into any of the holes that are present on the labyrinth board. The movement of the ball can be indirectly controlled by two knobs which change the orientation of the board. While it is a relatively straightforward game, it requires fine motor skills and spatial reasoning abilities, and, from experience, humans require a great amount of practice to become proficient at the game. Using recent advances in model-based reinforcement learning techniques, CyberRunner is able to outperform the previously fastest recorded time, achieved by an extremely skilled human player, by over 6%. Moreover, it does so with only 6 hours of practice. We envision expanding the capabilities of CyberRunner through further research. Students will contribute to advancing the field and establishing CyberRunner as a real-world robotic benchmark. Suitable projects in different areas are available for talented and motivated students. The project topics span model-based control, reinforcement learning, computer vision, and hardware design.
Keywords
Robotics, Reinforcement Learning, Machine Learning, Computer Vision, Control, Hardware Design
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Semester Project , Master Thesis
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Published since: 2024-01-12 , Earliest start: 2024-01-01 , Latest end: 2024-12-31
Organization Research D'Andrea
Hosts Bi Thomas
Topics Engineering and Technology