Ramin Tavakoli Kolagari

Transferable RL for Real-World Navigation Using Semantic Segmentation and Bird’s-Eye View Abstraction

Reinforcement Learning (RL) has shown significant promise in developing autonomous navigation algorithms for complex environments. However, the direct application of RL policies trained in simulation to real-world scenarios often faces challenges due to the reality gap. This paper proposes a two-sta