Ayesha Jena is a doctoral student in the Department of Computer Science at the Faculty of Engineering, LTH at Lund University. She received her Master's in Robotics from the University of Bristol, the United Kingdom in 2020. She started her Ph.D. in Computer Science with the Lund part of the collaborative ELLIT-funded (Excellence Centre at Linköping – Lund in Information Technology) project on Distributed Situation Awareness and Mixed-Initiative Interaction for Collaborative Robotics. Her research areas are currently focused on Human-Robot Interaction, Cognitive Robotics, and Artificial intelligence.

A brief about her work:

With Industry 5.0, it will become common to see robots actively collaborating with humans within workspaces. The challenge is to develop robots operating in shared spaces within unstructured environments. A promising approach to optimizing the operational performance of Human-Robot Interaction (HRI) is to consider the Mixed-Initiative approach in which tasks and authority of humans and agents are dynamically defined based on abilities.  

We aim to have an interaction and reasoning framework for effective HRI collaboration. In order to make these judgments, the system needs a reliable understanding of the overall situation (situation awareness), including underlying intentions of observable actions, and provide a framework for classifying various intentions, including initiation, movement, retrieval, idle observation, and composite intentions. This classification is a significant step in addressing one of the major challenges in HRI, which is bi-directional communication. This capability is pivotal in shaping the robot's behavior, ensuring effective communication of the user's intentions. In turn, it enhances the robot's ability to comprehend human intentions during goal execution, leading to natural and safe interactions between humans and robots. Intention reading, as we define it, encompasses the ability to precisely comprehend the objectives motivating the observable actions executed by others.  

Currently, I am using VR systems to have a framework for mixed-initiative interaction where we can collaborate and access humans’ intervention in these scenarios and provide useful insights into these interactions.