{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T01:59:33Z","timestamp":1779328773558,"version":"3.51.4"},"reference-count":17,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,2,4]]},"abstract":"<jats:p>In order to improve the trajectory tracking control effect of mobile robot, a mobile robot trajectory tracking control (TRC) method based on AVRX operating system is proposed. The principle of AVRX operating system is analyzed and the hardware structure of mobile robot is designed. The input-output relationship of mobile robot trajectory is determined according to multivariable fuzzy controller and the wrong data of mobile robot trajectory tracking information is eliminated by radar point cloud measurement. The TRC model of mobile robot is designed through Euler Lagrange equation to realize the TRC of mobile robot. The experimental results show that the trajectory tracking accuracy of mobile robot is as high as 97.9%, the trajectory tracking time is 16.2 s, and the trajectory tracking error of mobile robot is only 0.04. It shows that the TRC effect of mobile robot is improved, which provides a reference for the trajectory tracking control of mobile robots.<\/jats:p>","DOI":"10.3233\/jcm-226543","type":"journal-article","created":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T11:36:28Z","timestamp":1668166588000},"page":"253-265","source":"Crossref","is-referenced-by-count":2,"title":["Trajectory tracking control method of mobile robot based on AVRX operating system"],"prefix":"10.66113","volume":"23","author":[{"given":"Qiguo","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"7","key":"10.3233\/JCM-226543_ref1","first-page":"1125","article-title":"Robot TRC based on multi-sensor fusion","volume":"27","author":"Mao","year":"2020","journal-title":"Control Eng."},{"issue":"5","key":"10.3233\/JCM-226543_ref2","first-page":"87","article-title":"A single camera 360-degree real time vision-based localization 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