Drl-based navigation approaches in industrial robotics

Recently, mobile robots have become important tools in various industries, especially in logistics. Deep reinforcement learning emerged as an alternative planning method to replace overly conservative approaches and promises more efficient and flexible navigation. However, deep reinforcement learning approaches are not suitable for long-range navigation due to their proneness to local minima and lack of long-term memory, which hinders its widespread integration into industrial applications of mobile robotics. In this article, we propose a navigation system incorporating deep-reinforcementlearning-based local planners into conventional navigation stacks for long-range navigation of mobile robots. © 2021, VDI Fachmedien GmBH & Co. KG. All rights reserved.