Overarching research interest
My main research interest is how to include humans in the control loop of robotic systems for real-time control of complex physical interactions in unstructured and unpredictable environments. This entails the development of new human-robot interfaces and the integration of human models into robot control systems. To facilitate seamless human-robot interaction, I strive to create new robot control and learning methods that exploit direct human feedback as well as insight from the integrated models. The key areas within that interest are physical human-robot collaboration, teleimpedance (teleoperation with real-time impedance control), robotic physiotherapy, and human motor control.
Physical human-robot collaboration
One of my main areas of expertise is physical human-robot collaboration, where I focus on how to make robots understand human intentions and then control their physical actions in order to facilitate collaborative task executions. In this direction, the key element is to incorporate human behaviour and biomechanical models into the robot control system that enable real-time insight into human goals, internal states and ergonomics. Furthermore, I often incorporate machine learning methods that enable robots to gain new skills online while collaborating with humans. The main application areas I explore are collaborative manufacturing (e.g., assembly, polishing, sawing, etc.) and assistance in elderly care through the use of collaborative robots and exoskeletons.
Teleimpedance and remote robot teaching
Another important area of expertise is teleimpedance, which is a form of teleoperation that enables the human operator to remotely control the robot and its physical interaction through real-time changes of impedance. Commanding a proper impedance depending on the type of task and conditions can greatly simplify complex interactions with the remote environment and make them safer. For example, when interacting with humans or fragile objects, the robot can become less stiff (i.e., soft) in order to make sure no harm is done during the interaction. When something is perturbing the robot while executing a precise task, the stiffness can be increased to ensure the disturbances are rejected and the desired accuracy is maintained. In teleimpedance, I particularly focus on the development of interfaces that enable the human operator to command the impedance of the remote robot in real-time. Furthermore, I develop methods where teleimpedance can be used as a way to teach the remote robot complex interaction skill. The main application areas I explore are manufacturing (e.g., assembly, polishing, sawing, etc.), assistance in elderly care and inspection & maintenance, where remote robot control is needed.
Biomechanics-aware robotic physiotherapy
Additionally, I explore how to use collaborative robots as a tool for physical therapy of musculoskeletal injuries, where similar principles can be exploited. The key innovation in this direction is to create an abstraction of a complex biomechanical model that can be included in the robot control system and used in real-time to facilitate safe and effective physiotherapy. To this end, we developed an abstraction of a biomechanical model called the "strain map".
Human motor control
I am also interested in how humans control their movements and physical interactions since such insights can directly benefit the development of better robot control and teaching methods. In particular, I am studying how the human neuromechanical system derives, controls and optimises the movements of limbs and the body during physical interaction.