首页 /研究 /Path planning of mobile robots with Q-learning
LEARNING

Path planning of mobile robots with Q-learning

Halil Cetin, Akif Durdu

发表年份
2014
引用次数
10

摘要

Robotic systems which rapidly continue its development are increasingly used in our daily life. Mobile robots both draw the map where they may move in their environment and reach to the determined target in the shortest time by going on the shortest way in their prepared map. In this paper, Q-learning-based path planning algorithm is presented to find a target in the maps which are obtained by mobile robots. Q-learning is a kind of reinforcement learning algorithm that detects its environment and shows a system which makes decisions itself that how it can learn to make true decisions about reaching its target. The fact that a mobile robot truly finds targets that are located on different points in a few sample maps by processing our proposed Q-learning-based path planning algorithm is shown at the end of the paper.

关键词

Mobile robotMotion planningReinforcement learningRobotComputer scienceShortest path problemPath (computing)Artificial intelligenceQ-learningTheoretical computer science

相关论文

查看 LEARNING 分类全部论文