66 citations · 121 across the 6 of their papers we have counts for
5 papers · 1 filter
Obtaining Robust Control and Navigation Policies for Multi-Robot Navigation via Deep Reinforcement Learning
Christian Jestel, Hartmut Surmann, Jonas Stenzel +2
Multi-robot navigation is a challenging task in which multiple robots must be coordinated simultaneously within dynamic environments. We apply deep reinforcement learning (DRL) to…
Deployment of Aerial Robots during the Flood Disaster in Erftstadt / Blessem in July 2021
Hartmut Surmann, Dominik Slomma, Robert Grafe +1
Climate change is leading to more and more extreme weather events such as heavy rainfall and flooding. This technical report deals with the question of how rescue commanders can be…
Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments
Hartmut Surmann, Christian Jestel, Robin Marchel +3
Deep Reinforcement Learning has been successfully applied in various computer games [8]. However, it is still rarely used in real-world applications, especially for the navigation…
3D mapping for multi hybrid robot cooperation
Hartmut Surmann, Nils Berninger, Rainer Worst
This paper presents a novel approach to build consistent 3D maps for multi robot cooperation in USAR environments. The sensor streams from unmanned aerial vehicles (UAVs) and groun…
3D Registration of Aerial and Ground Robots for Disaster Response: An Evaluation of Features, Descriptors, and Transformation Estimation
Abel Gawel, Renaud Dubé, Hartmut Surmann +3
Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior informa…