6 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…
A Development Cycle for Automated Self-Exploration of Robot Behaviors
Thomas M. Roehr, Daniel Harnack, Hendrik Wöhrle +7
In this paper we introduce Q-Rock, a development cycle for the automated self-exploration and qualification of robot behaviors. With Q-Rock, we suggest a novel, integrative approac…
Combinatorics of a Discrete Trajectory Space for Robot Motion Planning
Felix Wiebe, Shivesh Kumar, Daniel Harnack +3
Motion planning is a difficult problem in robot control. The complexity of the problem is directly related to the dimension of the robot's configuration space. While in many theore…