Development of Deep Learning Algorithm for Humanoid Robots to Walk to the Target Using Semantic Segmentation and Deep Q Network

摘要

In this article, a new algorithm incorporating deep semantic segmentation algorithm and deep reinforcement algorithm is proposed to avoid the obstacle. This work was generated from two parts. The first part included semantic segmentation by using mini-Unet. The objects were detected and recognized. In the second part, Deep Q Network (DQN) was used for humanoid robots to learn to walk to target. The obtained results showed that the performance of proposed algorithm confirmed.