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cs.RO2021
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…
cs.RO2021
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…
cs.RO2021
Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systems
Linh Kästner, Teham Buiyan, Xinlin Zhao +3
Recently, mobile robots have become important tools in various industries, especially in logistics. Deep reinforcement learning emerged as an alternative planning method to replace…