Reconstructing the motion trajectory of an intelligent cart based on an upper unit

Jingwen Feng; Linjun Guo; Jinrong Huang

doi:10.1117/12.3050392

24 October 2024 Reconstructing the motion trajectory of an intelligent cart based on an upper unit

Jingwen Feng, Linjun Guo, Jinrong Huang

Proceedings Volume 13396, Third International Conference on Image Processing, Object Detection, and Tracking (IPODT 2024); 133960W (2024) https://doi.org/10.1117/12.3050392
Event: 3rd International Conference on Image Processing, Object Detection and Tracking (IPODT24), 2024, Nanjing, China

Abstract

The design of this paper employs the use of a scientific software, namely VOFA+, for the purpose of graphical debugging of embedded hardware, with the objective of producing the upper unit of the intelligent trolley. The upper unit establishes a Bluetooth connection to the intelligent trolley and is capable of modifying the control parameters of the intelligent trolley operation in real time. Additionally, it is able to plot the waveforms of the operation data in real time on the designated window. The upper unit, as designed in this paper, is capable of adjusting the PID parameters of the trolley in real time, viewing the waveform changes of the running data of the trolley directly in the drawing window, and determining the reasonability of the modified parameters. Additionally, the intelligent vehicle is equipped with a six-axis sensor MPU6050, which is reconfigured based on the obtained IMU data to track the cart's movement position and display its trajectory in real time to the upper unit. The data obtained from both the simulation and the actual test have been statistically analyzed, and it has been demonstrated that all the functions of the design have been achieved.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingwen Feng, Linjun Guo, and Jinrong Huang "Reconstructing the motion trajectory of an intelligent cart based on an upper unit", Proc. SPIE 13396, Third International Conference on Image Processing, Object Detection, and Tracking (IPODT 2024), 133960W (24 October 2024); https://doi.org/10.1117/12.3050392

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