72 citations · 322 across the 23 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning for Event-Triggered Control
Dominik Baumann, Jia-Jie Zhu, Georg Martius +1
Event-triggered control (ETC) methods can achieve high-performance control with a significantly lower number of samples compared to usual, time-triggered methods. These frameworks…
Evaluating Low-Power Wireless Cyber-Physical Systems
Dominik Baumann, Fabian Mager, Harsoveet Singh +2
Simulation tools and testbeds have been proposed to assess the performance of control designs and wireless protocols in isolation. A cyber-physical system (CPS), however, integrate…
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Fabian Mager, Dominik Baumann, Romain Jacob +3
Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals of tens of mi…
Event-triggered Learning for Resource-efficient Networked Control
Friedrich Solowjow, Dominik Baumann, Jochen Garcke +1
Common event-triggered state estimation (ETSE) algorithms save communication in networked control systems by predicting agents' behavior, and transmitting updates only when the pre…