2 publications
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Published Subscription Original Research
Improvement of Convergence Speed of Q-learning based Path Planning AlgorithmBy Murim Pak, Kangsong Ro, Choljin Wang, Jusong Pak
Abstract: Path planning is fundamental and important task of mobile robot. There are many attempts to adopt reinforcement learning (RL) in mobile robot path planning. RL based path planning is effective in path planning of intelligent mobile robot, especially in unknown environment because it doesn’t require environmental information and finds optimal path through trial-and-error process. Q-learning is one of RL algorithm widely used in path planning of mobile robots. The main …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article →
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Published Subscription Review Article
Path Planning using DDPG Algorithm and Univector Field Method for Intelligent Mobile RobotBy Jiyon Yun, Kangsong Ro, Jusong Pak, Choljin Wang
Abstract: Path planning is one of the most fundamental challenging tasks in robotics and its purpose is to lead the robot from the initial position to the goal without any collision through the optimal route. With the rapid development of artificial intelligence technology, AI has been widely studied for robot path planning and a method by deep reinforcement learning (DRL) was proposed. In general, path planning methods with DRL need discrete …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article →