Institute for Dynamic Systems and ControlOpen OpportunitiesMost control methods operate under the assumption of a known model. However, in practice, knowing the exact dynamics model a priori is unrealistic. A common approach is to model the unknown dynamics using Gaussian Processes (GPs) which can characterize uncertainty and formulate a Model Predictive Control (MPC) type problem. However, it is difficult to exactly utilize this uncertainty characterization in predictive control.
In a recent approach [1], we proposed a sampling-based robust GP-MPC formulation for accurate uncertainty propagation by sampling continuous functions. In contrast, in the proposed project, you will implement an approximation method for sampling continuous functions using a finite number of basis functions [2] and solve the MPC problem jointly with the sampled dynamics. You will analyze the trade-offs between performance, approximation accuracy, and computational cost for this method. - Engineering and Technology
- Master Thesis, Semester Project
| The reintegration of individuals who have experienced accidents is at the heart of our efforts. A severe car accident or a workplace accident, can profoundly change a person's life. Such tragic events often result in serious injuries, such as severed limbs, and are classified as "polytrauma." At our lab, we are working to mitigate the consequences of such severe accidents. Using an innovative perfusion machine, we try to keep severed limbs alive outside the body for up to four days. This time window provides the foundation for successfully retransplanting the limb to a stabilized polytrauma patient. - Biomedical Engineering, Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis
| Development of an open-source Python toolbox for optimizing electric bus fleet electrification in Switzerland, focusing on charging infrastructure, battery sizing, and strategy. The next phase aims to enhance compatibility, expand charging options, integrate new energy sources, and improve computational efficiency in collaboration with PostAuto. - Mechanical Engineering
- Master Thesis
| Mobility is typically self-optimized for a particular region to accommodate internal travel needs. However, as soon as one considers multiple, interacting regions (e.g., urban areas interacting with agglomerations, and agglomerations interacting with rural areas), important coordination issues occur, including scheduling mismatches, fleet allocations, and congestion peaks. In short, a mobility system composed of self-optimized mobility systems seems to often operate suboptimally.
In this project, we will investigate the idea of strategic interactions of future mobility stakeholders across heterogeneous regions, such as urban areas, agglomerations, and rural areas, leveraging techniques from network design, optimization, game theory, and policy making. - Automotive Engineering, Information, Computing and Communication Sciences, Mathematical Sciences, Mechanical and Industrial Engineering, Transport Engineering
- Master Thesis, Semester Project
| In this semester thesis, our goal is to enable an F1Tenth car, an autonomous vehicle at 1:10 scale of a Formula 1 car, to race safely on a track that is perceived through RGB-D images captured by an onboard camera. - Engineering and Technology
- Semester Project
| This project aims to improve the design of predictive controllers that robustly ensure safe operation for a large class of uncertain nonlinear systems. - Dynamical Systems, Systems Theory and Control
- ETH Zurich (ETHZ), Master Thesis
| This thesis explores advanced energy management for hybrid ships using Dynamic Programming (DP) and Model Predictive Control (MPC). It integrates Long Short-Term Memory (LSTM) models aiming to improve load forecasting, energy demand prediction, and operational optimization, with a focus on real-world constraints and maritime applications. - Engineering and Technology
- Master Thesis
| This project aims to develop an online learning framework for achieving precise position control of a soft robotic arm while adapting to time-varying system dynamics. - Engineering and Technology
- Master Thesis
| MOTIVATION ⇾ Creating a digital twin of the robot's environment is crucial for several reasons:
1. Simulate Different Robots: Test various robots in a virtual environment, saving time and resources.
2. Accurate Evaluation: Precisely assess robot interactions and performance.
3. Enhanced Flexibility: Easily modify scenarios to develop robust systems.
4. Cost Efficiency: Reduce costs by identifying issues in virtual simulations.
5. Scalability: Replicate multiple environments for comprehensive testing.
PROPOSAL
We propose to create a digital twin of our Semantic environment, designed in your preferred graphics Platform to be able to simulate Reinforcement Learning agents in the digital environment, to create a unified evaluation platform for robotic tasks. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| The goal of the project consists in deriving error bounds for the approximate Gaussian process regression method given by the FITC method. - Engineering and Technology
- Master Thesis, Semester Project
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