Development of Deep Learning Algorithm for Humanoid Robots to Walk to the Target Using Semantic Segmentation and Deep Q Network - Aslan, Simge Nur; Ucar, Aysegul; Guzelis, Cuneyt (Institute of Electrical and Electronics Engineers Inc., 2020)
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. © 2020 IEEE.
Anlamsal Bölütleme ve Derin Q Agi Kullanarak Hedefe Do?ru Yürümek Için Yeni Bir Derin Ö?renme Algoritmasinin Geliştirilmesi
2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 -- 15 October 2020 through 17 October 2020 -- Istanbul -- 165305
Keywords: deep Q network; deep reinfrocement learnig; humanoid robots; semantic segmentation