A hybrid reinforcement learning strategy informed by RRT∗ for path planning of mobile robots in open-pit mining

This work introduces a hybrid path planning strategy for differential-drive robotic vehicles, combining reinforcement learning methods with sampling techniques. Specifically, Q-Learning (QL) is used to find a global path by exploring and exploiting enviro