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http://dx.doi.org/10.5392/JKCA.2019.19.12.164

Implementation of Autonomous Mobile Wheeled Robot for Path Correction through Deep Learning Object Recognition  

Lee, Hyeong-il (김포대학교 CIT융합학부 컴퓨터소프트웨어과)
Kim, Jin-myeong (김포대학교 CIT융합학부 컴퓨터소프트웨어과)
Lee, Jai-weun ((주)솔엔비)
Publication Information
The Journal of the Korea Contents Association / v.19, no.12, 2019 , pp. 164-172 More about this Journal
Abstract
In this paper, we implement a wheeled mobile robot that accurately and autonomously finds the optimal route from the starting point to the destination point based on computer vision in a complex indoor environment. We get a number of waypoints from the starting point to get the best route to the target through deep reinforcement learning. However, in the case of autonomous driving, the majority of cases do not reach their destination accurately due to external factors such as surface curvature and foreign objects. Therefore, we propose an algorithm to deepen the waypoints and destinations included in the planned route and then correct the route through the waypoint recognition while driving to reach the planned destination. We built an autonomous wheeled mobile robot controlled by Arduino and equipped with Raspberry Pi and Pycamera and tested the planned route in the indoor environment using the proposed algorithm through real-time linkage with the server in the OSX environment.
Keywords
Wheeled Mobile Robot; Path Finding; Deep Reinforcement Learning; Deep Learning; Autonomous Driving Robot;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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