Leveraging motion perceptibility and deep reinforcement learning for visual control of nonholonomic mobile robots

Takieddine Soualhi, Nathan Crombez, Alexandre Lombard, Yassine Ruichek, Stéphane Galland

Abstract: Highlights•A DRL method is proposed to address the visual control of nonholonomic mobile robots.•A novel auxiliary task for prediction motion perceptibility values from input images.•Validation and evaluation of the proposed approach in both simulated and real-world environments.