This work presents a Deep Reinforcement Learning algorithm to control a differentially
driven mobile robot. This study seeks to explain the influence of different definitions of the …

Reinforcement learning approach has been preferred by researchers and scientists in
recent years, especially due to its superior performance in robot studies. While smart …

This article describes the use of the Deep Deterministic Policy Gradient network, a deep
reinforcement learning algorithm, for mobile robot navigation. The neural network structure …

This paper presents a study of a deep reinforcement learning technique that uses a Deep
Deterministic Policy Gradient network for application in navigation of mobile robots. In order …

This article proposes the use of reinforcement learning (RL) algorithms to control the
position of a simulated Kephera IV mobile robot in a virtual environment. The simulated …

Deep reinforcement learning continues to explore in the environment and adjusts the neural
network parameters by the reward function. The actual production line can not be used as …

The Reinforcement Learning is a subset of machine learning that deals with learning
decisions from rewards given by the environment. The model classic reinforcement learning …

Deep reinforcement learning (DRL) has the ability to learn and solve complex and
challenging tasks when compared to traditional robot navigation methods. In this study …

Mobile robotics is one of the emerging research area in the robotics. The recently evolving
techniques, artificial intelligence and precise hardware controller design gave new scope in …

This paper provides a study of two deep reinforcement learning techniques for application in
navigation of mobile robots, one of the techniques is the Soft Actor Critic (SAC) that is …