Path planning is the most fundamental necessity for autonomous mobile robots.
Traditionally, the path planning problem was solved using analytical methods, but these …

Many optimization methods for construction site layout planning (CSLP) generate the
shortest path of workers to calculate traveling costs and site safety performance. However …

The use of a robot cleaner for manure removal improves housing conditions for dairy cows
in the face of labor shortages. However, current robot cleaners follow programmed fixed …

As the demand for autonomous driving increases, it is paramount to ensure safety. Early
accident prediction using deep learning methods for driving safety has recently gained much …

An automated condition monitoring (CM) framework is essential for outdoor mobile robots to
trigger prompt maintenance and corrective actions based on the level of system …

Transformer is a state-of-the-art model in the field of natural language processing (NLP).
Current NLP models primarily increase the number of transformers to improve processing …

This article presents an end-to-end path planning and motion control method based on deep
reinforcement learning (DRL), aimed at enhancing the autonomous navigation capabilities …

This paper presents a technique to train a robot to perform kick-motion in AI soccer by using
reinforcement learning (RL). In RL, an agent interacts with an environment and learns to …

Robots find extensive applications in industry. In recent years, the influence of robots has
also increased rapidly in domestic scenarios. The Q-learning algorithm aims to maximise the …

In replacing fossil fuels with renewable energy resources for carbon neutrality, the
unbalanced resource production of intermittent wind and photovoltaic (PV) power is a critical …