38 citations · 39 across the 4 of their papers we have counts for
4 papers
Holistic Deep-Reinforcement-Learning-based Training of Autonomous Navigation Systems
Linh Kästner, Marvin Meusel, Teham Bhuiyan +1
In recent years, Deep Reinforcement Learning emerged as a promising approach for autonomous navigation of ground vehicles and has been utilized in various areas of navigation such…
Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments
Linh Kästner, Reyk Carstens, Huajian Zeng +5
Following up on our previous works, in this paper, we present Arena-Rosnav 2.0 an extension to our previous works Arena-Bench and Arena-Rosnav, which adds a variety of additional m…
Deep-Reinforcement-Learning-based Path Planning for Industrial Robots using Distance Sensors as Observation
Teham Bhuiyan, Linh Kästner, Yifan Hu +2
Industrial robots are widely used in various manufacturing environments due to their efficiency in doing repetitive tasks such as assembly or welding. A common problem for these ap…
Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environments
Linh Kästner, Teham Bhuiyan, Tuan Anh Le +9
The ability to autonomously navigate safely, especially within dynamic environments, is paramount for mobile robotics. In recent years, DRL approaches have shown superior performan…