Shared Autonomy

Shared autonomy aims to improve human-robot collaboration by combining human control with autonomous robotic assistance, optimizing both task performance and user experience. Current research emphasizes developing algorithms that dynamically adjust the level of autonomy based on factors like human skill, task complexity, and user feedback, often employing reinforcement learning, diffusion models, or potential field methods to achieve this. This field is significant for enhancing human capabilities in various domains, from assistive robotics for people with disabilities to improving efficiency and safety in industrial settings. The focus is on creating intuitive and safe interfaces that allow seamless transitions between autonomous and human control, addressing issues of trust, cognitive load, and effective communication between human and robot.