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Development of Stair Climbing Robot for Delivery Based on Deep Learning  

Mun, Gi-Il (School of Mechatronics Engineering, Korea University of Technology and Education)
Lee, Seung-Hyeon (School of Mechatronics Engineering, Korea University of Technology and Education)
Choo, Jeong-Pil (School of Mechatronics Engineering, Korea University of Technology and Education)
Oh, Yeon-U (School of Mechatronics Engineering, Korea University of Technology and Education)
Lee, Sang-Soon (School of Mechatronics Engineering, Korea University of Technology and Education)
Publication Information
Journal of the Semiconductor & Display Technology / v.21, no.4, 2022 , pp. 121-125 More about this Journal
Abstract
This paper deals with the development of a deep-learning-based robot that recognizes various types of stairs and performs a mission to go up to the target floor. The overall motion sequence of the robot is performed based on the ROS robot operating system, and it is possible to detect the shape of the stairs required to implement the motion sequence through rapid object recognition through YOLOv4 and Cuda acceleration calculations. Using the ROS operating system installed in Jetson Nano, a system was built to support communication between Arduino DUE and OpenCM 9.04 with heterogeneous hardware and to control the movement of the robot by aligning the received sensors and data. In addition, the web server for robot control was manufactured as ROS web server, and flow chart and basic ROS communication were designed to enable control through computer and smartphone through message passing.
Keywords
Deep learning; YOLOv4; ROS operating system; Stair climbing robot; ROS web server;
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