Parallel Reinforcement Learning Simulation for Visual Quadrotor Navigation
Jack Saunders,Sajad Saeedi,Wenbin Lil,Jack Saunders,Sajad Saeedi,Wenbin Lil
Reinforcement learning (RL) is an agent-based approach for teaching robots to navigate within the physical world. Gathering data for RL is known to be a laborious task, and real-world experiments can be risky. Simulators facilitate the collection of training data in a quicker and more cost-effective manner. However, RL frequently requires a significant number of simulation steps for an agent to be...
