5 papers
Iterative linear quadratic regulator on SU(N) for multi-qubit gate synthesis
Dirk Heimann, Felix Wiebe, Elie Mounzer +1
In quantum optimal control theory, gradient-based trajectory optimization techniques have proven versatile in designing multi-qubit quantum gates. Furthermore, incorporating the un…
Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking
Franek Stark, Felix Wiebe, Shubham Vyas +2
This paper presents a multi-phase whole-body model predictive control (MPC) approach for bipedal walking, combining a detailed whole-body model in the near horizon with a simplifie…
Iterative Linear Quadratic Regulator for Quantum Optimal Control
Dirk Heimann, Felix Wiebe, Tahereh Abad +4
Quantum optimal control for gate optimization aims to provide accurate, robust, and fast pulse sequences to achieve gate fidelities on quantum systems below the error correction th…
Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd 'AI Olympics with RealAIGym' Competition
Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera +17
In the field of robotics many different approaches ranging from classical planning over optimal control to reinforcement learning (RL) are developed and borrowed from other fields…
Quantum Deep Reinforcement Learning for Robot Navigation Tasks
Hans Hohenfeld, Dirk Heimann, Felix Wiebe +1
We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity. For this, we train p…