Design of two-wheel self-balancing vehicle based on visual identification

Clicks: 193
ID: 24939
2019
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Ranked #16 of 37 articles by views in eurasip journal on image and video processing

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Abstract
Abstract Poor user experience is caused by the current unstable operation of the two-wheel self-balancing vehicle control system, the high failure rate, and the poor accuracy and sensitivity of the control system (prone to deviation). Therefore, the work studied the two-wheel self-balancing vehicle system with the visual recognition of vehicle attitude. Kalman filtering and PID control algorithm were adopted to reduce the high frequency interference of the accelerometer and the low frequency error of the gyroscope, improve the response speed and control precision of motor to error, and ensure vertical control. The road images were acquired by a charge-coupled device vision sensor with the edge information extracted by the Laplacian operator, which ensures autonomous navigation control of a balance car. Based on the calculation of the distance between road axis and the existence detection of forward obstacles, the early warning mechanism was established through the calculation of the group agent to improve the safety performance of a balance vehicle. Experiments showed the improved control system has good stability, fast walking speed, strong anti-interference, and high security.
Reference Key
zhang2019designeurasip Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhang, Boping;Wu, Guoxi;
Journal eurasip journal on image and video processing
Year 2019
DOI
DOI not found
URL
http://link.springer.com/article/10.1186/s13640-019-0434-7
Keywords Keywords not found

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