6 citations · 6 across the 8 of their papers we have counts for
5 papers · 1 filter
A General Safety Framework for Autonomous Manipulation in Human Environments
Jakob Thumm, Julian Balletshofer, Leonardo Maglanoc +2
Autonomous robots are projected to significantly augment the manual workforce, especially in repetitive and hazardous tasks. For a successful deployment of such robots in human env…
Stepping Out of the Shadows: Reinforcement Learning in Shadow Mode
Philipp Gassert, Matthias Althoff
Reinforcement learning (RL) is not yet competitive for many cyber-physical systems, such as robotics, process automation, and power systems, as training on a system with physical c…
Text2Interaction: Establishing Safe and Preferable Human-Robot Interaction
Jakob Thumm, Christopher Agia, Marco Pavone +1
Adjusting robot behavior to human preferences can require intensive human feedback, preventing quick adaptation to new users and changing circumstances. Moreover, current approache…
Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking
Roland Stolz, Hanna Krasowski, Jakob Thumm +3
Continuous action spaces in reinforcement learning (RL) are commonly defined as multidimensional intervals. While intervals usually reflect the action boundaries for tasks well, th…
Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea
Hanna Krasowski, Matthias Althoff
For safe operation, autonomous vehicles have to obey traffic rules that are set forth in legal documents formulated in natural language. Temporal logic is a suitable concept to for…