Obstacle Avoidance in Dynamic Environment: a Hierarchical Solution

Abstract

This article presents a concept for obstacle avoidance in dynamic environment suitable for mobile robot. The task of obstacle avoidance is divided in three principal groups: local, global and for emergencies. The local avoidance is here approached, in which the concept used is based on reinforcement learning, in such a way that the situations are divided into four states and two kinds of actions are possible. The states define in what situation the movement relationship between the robot and the dynamic obstacles is present, and the actions decide in which direction the robot must follow, in order to avoid a possible collision. And besides, here it is showed also how the state-action matrix was filled and its representation using neural network.