MATEC Web Conf.
Volume 336, 20212020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|Number of page(s)||10|
|Section||Design and Control of Intelligent Robotics|
|Published online||15 February 2021|
Binocular intelligent following robot based on YOLO-LITE
Nanjing University of Posts and Telecommunications School of Modern Posts, Nanjing, 210003, China
* Corresponding author: firstname.lastname@example.org
In order to solve the problem that the deep neural network model is large in scale, the calculation time is too long, and the real-time performance is severely limited when combined with embedded devices, so studied the intelligent follower robot system based on YOLO-LITE algorithm combined with Raspberry Pi 3B+. The system mainly includes camera processing, target detection and other modules. Obtained the internal and external parameters of the camera through calibration, and according to these parameters to correct the binocular camera. Recognized and located the target in each frame of image, calculated the distance from the camera to the target and the center location error, and driven the car to move. The experimental results show that the following car has excellent real-time performance, the average detection frame rate can reach 20Fps, and the average detection accuracy can reach more than 80%.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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