most citedProvably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments

2 citations · 3 across the 2 of their papers we have counts for

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cs.RO2024

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…

cs.RO2022★ 2 cited

Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments

Jakob Thumm, Matthias Althoff

Deep reinforcement learning (RL) has shown promising results in the motion planning of manipulators. However, no method guarantees the safety of highly dynamic obstacles, such as h…