4 citations · 4 across the 5 of their papers we have counts for
10 papers · 1 filter
Arena 3.0: Advancing Social Navigation in Collaborative and Highly Dynamic Environments
Linh Kästner, Volodymyir Shcherbyna, Huajian Zeng +8
Building upon our previous contributions, this paper introduces Arena 3.0, an extension of Arena-Bench, Arena 1.0, and Arena 2.0. Arena 3.0 is a comprehensive software stack contai…
Mono Video-Based AI Corridor for Model-Free Detection of Collision-Relevant Obstacles
Thomas Michalke, Yassin Kaddar, Thomas Nürnberg +2
The detection of previously unseen, unexpected obstacles on the road is a major challenge for automated driving systems. Different from the detection of ordinary objects with pre-d…
Obstacle-aware Waypoint Generation for Long-range Guidance of Deep-Reinforcement-Learning-based Navigation Approaches
Linh Kästner, Xinlin Zhao, Zhengcheng Shen +1
Navigation of mobile robots within crowded environments is an essential task in various use cases, such as delivery, health care, or logistics. Deep Reinforcement Learning (DRL) em…
All-in-One: A DRL-based Control Switch Combining State-of-the-art Navigation Planners
Linh Kästner, Johannes Cox, Teham Buiyan +1
Autonomous navigation of mobile robots is an essential aspect in use cases such as delivery, assistance or logistics. Although traditional planning methods are well integrated into…
Enhancing Navigational Safety in Crowded Environments using Semantic-Deep-Reinforcement-Learning-based Navigation
Linh Kästner, Junhui Li, Zhengcheng Shen +1
Intelligent navigation among social crowds is an essential aspect of mobile robotics for applications such as delivery, health care, or assistance. Deep Reinforcement Learning emer…
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint Generators
Linh Kästner, Teham Buiyan, Xinlin Zhao +3
Deep Reinforcement Learning has emerged as an efficient dynamic obstacle avoidance method in highly dynamic environments. It has the potential to replace overly conservative or ine…