Point Cloud Based Reinforcement Learning for Sim-to-Real and Partial Observability in Visual Navigation
Kenzo Lobos-Tsunekawa,Tatsuya Harada,Kenzo Lobos-Tsunekawa,Tatsuya Harada
Reinforcement Learning (RL), among other learning-based methods, represents powerful tools to solve complex robotic tasks (e.g., actuation, manipulation, navigation, etc.), with the need for real-world data to train these systems as one of its most important limitations. The use of simulators is one way to address this issue, yet knowledge acquired in simulations does not work directly in the real...
