PhD Position: Robust and Adaptive Control of Wearable Robotic Exoskeletons in Face of Uncertainty

Exoskeletons are wearable robots that assist human standing and walking. Such devices provide support to people who have sensory and motor disorders due to spinal cord injury. Due to limitations in currently used controllers for exoskeletons, like trajectory playback, users still need crutches at all times to maintain their balance and ensure their safety.

The goal of this project is to develop a robust model-based force controller that achieves human-like balance and walking without needing crutches. However, whether such a controller would always be stable in the face of uncertainty in both the exoskeleton, user and environment, is unknown. The user's weight changes every day, user joint stiffness depends on temperature or on the progression of the motor disorder. The location and stiffness of the floor might be uncertain and change significantly during use; an indoor surface could be hard but slippery, while a grassy field can be soft. We want to develop provably robust controllers that are able to take all these variations into account.

Job description

We are looking for a highly motivated PhD candidate to strengthen our research group. You will work in a multidisciplinary setting to bring together aspects from robust control, rigid and flexible body mechanics, machine learning and simulation. Specifically you will 1) investigate the stability and performance of new and state-of-the art exoskeleton control methods; 2) propose novel methods for synthesizing customized controllers with adaptable robustness; 3) improve our fundamental view of control of human-robot interactions from a robust control perspective.

We aim to participate in the Cybathlon 2024 Exoskeleton race. Because your work will focus on the robust balance control of the used exoskeleton, we expect you to join our Cybathlon team as one of the control software developers!