Human Exoskeleton Interaction

Human-exoskeleton interaction research focuses on optimizing the collaboration between humans and wearable robotic exoskeletons, aiming to create safe, intuitive, and effective assistive devices. Current efforts concentrate on developing accurate models of this interaction, often employing dynamic simulations and machine learning techniques like Gaussian processes to estimate forces and predict user behavior, and using these models to design controllers that minimize unwanted forces and enhance user comfort and performance. This work is crucial for improving exoskeleton design and control, leading to advancements in rehabilitation, assistive technologies, and human augmentation, with potential applications ranging from gait training to assisting individuals with mobility impairments.