25 citations · 53 across the 18 of their papers we have counts for
7 papers · 1 filter
Bridging the Model-Reality Gap with Lipschitz Network Adaptation
Siqi Zhou, Karime Pereida, Wenda Zhao +1
As robots venture into the real world, they are subject to unmodeled dynamics and disturbances. Traditional model-based control approaches have been proven successful in relatively…
RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks
Lukas Brunke, Siqi Zhou, Angela P. Schoellig
In this work we address the problem of performing a repetitive task when we have uncertain observations and dynamics. We formulate this problem as an iterative infinite horizon opt…
Fly Out The Window: Exploiting Discrete-Time Flatness for Fast Vision-Based Multirotor Flight
Melissa Greeff, Siqi Zhou, Angela P. Schoellig
Current control design for fast vision-based flight tends to rely on high-rate, high-dimensional and perfect state estimation. This is challenging in real-world environments due to…
safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics
Zhaocong Yuan, Adam W. Hall, Siqi Zhou +4
In recent years, both reinforcement learning and learning-based control -- as well as the study of their safety, which is crucial for deployment in real-world robots -- have gained…
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Lukas Brunke, Melissa Greeff, Adam W. Hall +4
The last half-decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learni…
Tomographic Witnessing and Holographic Quantifying of Coherence
Bang-Hai Wang, Si-Qi Zhou, Zhihao Ma +1
The detection and quantification of quantum coherence play significant roles in quantum information processing. We present an efficient way of tomographic witnessing for both theor…
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control
Jacopo Panerati, Hehui Zheng, SiQi Zhou +3
Robotic simulators are crucial for academic research and education as well as the development of safety-critical applications. Reinforcement learning environments -- simple simulat…