Development of Push-Recovery control system for humanoid robots using deep reinforcement learning

Development of Push-Recovery control system for humanoid robots using deep reinforcement learning

This paper focuses on the push-recovery problem of bipedal humanoid robots affected by external forces and pushes. Since they are structurally unstable, balance is the most important problem in humanoid robots. Our purpose is to design and implement a completely independent push-recovery control sys...

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Bibliographic Details
Main Authors: Emrah Aslan, Muhammet Ali Arserim, Ayşegül Uçar
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:Ain Shams Engineering Journal
Subjects:
Deep reinforcement learning
deep q network(DQN)
double deep q network(DDQN)
Humanoid robot
Robotis op2
Push-recovery
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447923000564

Internet

http://www.sciencedirect.com/science/article/pii/S2090447923000564

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