In this paper, a deep reinforcement learning algorithm is presented to control a humanoid
robot. We have used two control levels in a hierarchical manner. Within the high-level …

This book covers basic concepts of Artificial Intelligence, going through Machine Learning
and deepening RL, in a theoretical and practical way. Throughout the chapters, there are …

Focusing on the ball double-screw hydraulic knee joint as the research object, this paper
analyzes the load driving performance of the hydraulic knee joint. Taking the posture data of …

This paper presents a 3 Degrees-of-Freedom (DoF) rocket landing model environment,
controlled by an agent trained with the Proximal Policy Optimization (PPO) reinforcement …

This paper presents an approach to designing the controller for the swing up cart pole
problem. The approach used to solve the problem is a method based on Deep …

In this work, we use a virtual learning framework for the IEEE's Very Small Size Soccer
(VSSS) competition based on Deep Reinforcement Learning (DRL) to train and improve the …

Abstract The integration of Deep Reinforcement Learning (DRL) into the realm of robotics
and autonomous systems has emerged as a groundbreaking paradigm shift, empowering …

This paper describes the communication system in the pattern of soccer games on the
humanoid robot R-SCUAD. The communication system is an important part in the game of …

In this chapter, the most recent applications of Reinforcement Learning (RL) and how this
technique impacts various areas of knowledge are explored. Examples of RL applications in …

Ingress task is crucial in a humanoid robot's attempt to drive a land vehicle and reach its
destination fast. Previous work is inefficient in granting robots the ability to enter a vehicle …