Soft Manipulator

Soft manipulators, robots constructed from flexible materials, are being developed to achieve safer and more adaptable interaction with their environment, particularly in applications like surgery and assistive care. Current research emphasizes accurate force and position estimation, often employing model-based approaches (e.g., Cosserat rod theory, finite element methods) combined with machine learning techniques (e.g., Kalman filters, neural networks) to overcome challenges posed by the manipulators' inherent flexibility and underactuation. These advancements are improving control precision and enabling more complex tasks, leading to significant potential for improved robotic surgery, human-robot collaboration, and other applications requiring delicate and safe interaction.