Grad seminar: preference and performance-based adaptive task planning in human-robot collaboration
Abstract
This thesis delves into a central challenge in human-robot collaboration (HRC): the adaptive task planning of robots to enhance team performance, fluency, and the human agent's perception of both the robot and the collaboration. This thesis tackles the challenge of proactive task planning and allocation in collaborative scenarios, involving a single human and a single robot working together to accomplish a task. Recognizing the existing gaps in the literature, our focus revolves around balancing human agents' leading/following preferences and their performance, with the aim of fostering collaboration while maintaining a high level of human perception of the robot. The validation through user studies offers valuable insights, laying the groundwork for future research and applications in the continually evolving domain of human-robot collaboration.
Presenter
Ali Noormohammadi Asl, PhD candidate in Systems Design Engineering