Emmanuel Senft

Assistive robotics

My current research at Idiap focuses on assistive robotics, exploring how robots such as the Lio robot can help people in need.

Natural interfaces for robotic autonomy

During the NASA ULI Effective Human-Robot Teaming to Advance Aviation Manufacturing project, we developped new flexible automation paradigms based on Human-Robot collaboration for aircraft manufacturing. With these systems, we can benefit from both the robots' ability to realize repetitive and streneous tasks, and the human flexibility to detect what can be done and if the process is success.

I was postdoc on this project, and my role was to coordinate and integrate work from a team of graduate students and project assistants. On top of this integration work, I research new interfaces and workflows to allow for flexible authoring of rich robotic behaviors by shop floor workers.

In Situ Live Programming for Human-Robot Collaboration (published at UIST 2021)

High-level remote teleoperation of robots (published in Frontiers in Robotics and AI)

Learning social strategies in teaching

To teach robots to interact with humans, during my PhD, I developed SPARC (for Supervised Progressively Autonomous Robot Competencies), a learning paradigm to teach robots policies in real world interactions. SPARC uses interactive machine learning and keeps a human in the action selection loop to ensure that each action executed by the robot is correct even in the early stages of the learning. SPARC relies on a selection/suggestion/correction mechanism whereby the human can select actions for the robot, the robot can suggest an action to the human who can either passively accept the action and let it be executed after a small delay or prevent it. This allow to rely importantly on the human at the start of the interaction when the robot is still learning how to interact. Then, as the robot improves its policy, its autonomy can increase, thus reducing need for the human to select actions for the robot. The main outcome of the research can be found here.

Long-Term Human-Robot Interaction for Cardiac Rehabilitation

This project is a collaboration between our team in the University of Plymouth and the Marcela Munera and Carlos A. Cifuentes in Colombian School of Engineering Julio Garavito focused on how Socially Assistive Robots could help patients to adhere better to a cardiac rehabilitation. The main question of this project was to found out factors or information that the robot could use to help motivate patient with the rehabilitation through continual monitoring, social feedback and personalization. Additional information can be found here, full results are under review.