Projects concluded or in progress as a part of my PhD.
[Ongoing Project] Learning unconstrained and stable imitation policies from state-only expert demonstrations applicable to a variety of robotic platforms. Experiments and simulations are entirely conducted in Nvidia Isaac Lab and Isaac Gym. The project is funded by a competitive scholarship from the Swiss National Centres of Competence in Research (NCCR Automation) in collaboration with EPFL.
[Ongoing Project] Learning model-free reinforcement learning policies with internal safety and stability guarantees mainly for manipulation and locomotion tasks. The experiments leverage domain randomization and sim-to-real capabilities of Isaac Sim and Isaac Lab simulators. The project is in collaboration with Mitacs, funded by the Mitacs Accelerate Fellowship and an industrial partner, Sycodal Electronics Inc.
Learning polynomial imitation policies with guaranteed stability and out of distribution recovery.
Learning globally stable neural imitation policies (SNDS).
