Modified Q-learning with distance metric and virtual target on path planning of mobile robot

Ee, Soong Low and Ong, Pauline and Cheng, Yee Low and Omar, Rosli (2020) Modified Q-learning with distance metric and virtual target on path planning of mobile robot. Expert Systems with Applications, 199. ISSN 0957-4174

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Path planning is an essential element in mobile robot navigation. One of the popular path planners is Q-learning – a type of reinforcement learning that learns with little or no prior knowledge of the environment. Despite the successful implementation of Q-learning reported in numerous studies, its slow convergence associated with the curse of dimensionality may limit the performance in practice. To solve this problem, an Improved Q-learning (IQL) with three modifications is introduced in this study. First, a distance metric is added to Q-learning to guide the agent moves towards the target. Second, the Q function of Q-learning is modified to overcome dead-ends more effectively. Lastly, the virtual target concept is introduced in Q-learning to bypass dead-ends. Experi�mental results across twenty types of navigation maps show that the proposed strategies accelerate the learning speed of IQL in comparison with the Q-learning. Besides, performance comparison with seven well-known path planners indicates its efficiency in terms of the path smoothness, time taken, shortest distance and total distance used.

Item Type: Article
Uncontrolled Keywords: Moving target; obstacle avoidance; path planning; Q-learning; reinforcement learning; mobile robot
Subjects: T Technology > T Technology (General)
Depositing User: Mr. Abdul Rahim Mat Radzuan
Date Deposited: 14 Jun 2022 02:08
Last Modified: 14 Jun 2022 02:08

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