Neuroevolution for Navigation

In this work, we evolve neural network policies via mutation and recombination for dynamic obstacle avoidance. Traditonal approaches to mobile robot motion planning invovlves computationally expensive steps - mapping and planning. However, in this exploratory work, we simply map perceptions to actions using neural network policies and evolve them for dynamic obstacle avoidance.