Sim-To-Real Exoskeleton Control using Machine learning

Master thesis

Exoskeletons are wearable devices that assist or enhance movement, helping people with mobility issues and reducing strain in industrial jobs. Advanced control strategies optimize their performance by improving movement and saving energy. Simulation allows for quick and safe testing of these strategies, without the need for physical trials. It also helps ensure that exoskeletons work effectively and safely. This approach ensures better results before real-world implementation.