Improving robot navigation in crowded environments using intrinsic rewards
Diego Martinez-Baselga,Luis Riazuelo,Luis Montano,Diego Martinez-Baselga,Luis Riazuelo,Luis Montano
Autonomous navigation in crowded environments is an open problem with many applications, essential for the coexistence of robots and humans in the smart cities of the future. In recent years, deep reinforcement learning approaches have proven to outperform model-based algorithms. Nevertheless, even though the results provided are promising, the works are not able to take advantage of the capabilit...
