Minimally Invasive

Minimally invasive surgery (MIS) research focuses on improving precision, safety, and automation through robotic assistance and advanced imaging techniques. Current efforts concentrate on developing robust control architectures for robotic systems, including vision-based force estimation using deep learning models (e.g., encoder-decoder networks, recurrent neural networks) and constrained motion planning algorithms (e.g., hierarchical quadratic programming) to prevent tissue damage. These advancements aim to enhance surgical dexterity, improve haptic feedback, and ultimately lead to better patient outcomes by enabling more precise and controlled procedures.