Vision based trajectory following robot and swarm

Haque, I.; Arabi, Abul Al; Hossain, Shadat; Proma, Tanjina Piash; Uzzaman, Nafi; Amin, M. Ashraful

doi:10.1109/iccre.2017.7935037

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…In [4], Gomes et al applied the PID control algorithm for their line-following mobile robot. The input parameters of the line-following AGV include 𝑝 𝑒 and 𝜃 𝑒 as shown in (3). However, the parameter 𝑝 𝑒 is regarded as constant in [4] to implement the PID controller.…”

Section: Line-following Controlmentioning

confidence: 99%

“…With its popularity and efficiency, the PID (Proportional Integral Derivative) controller has been widely applied to linefollowing AGV studies [1][2][3][4][5]. In addition, control methods such as MSE controller (mean-square error controller) [6], visual controller [7], fuzzy controller [8][9][10][11], neural network [12], rotary controller [13], sliding mode controller [14,15] and adaptive controller [16,17] have also been used for AGV navigation.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism

Bach

2022

Journal of Robotics and Control

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Recently, there has been increasing attention paid to AGV (Automated Guided Vehicle) in factories and warehouses to enhance the level of automation. In order to improve productivity, it is necessary to increase the efficiency of the AGV, including working speed and accuracy. This study presents a fuzzy-PID controller for improving the efficiency of a line-following AGV. A line-following AGV suffers from tracking errors, especially on curved paths, which causes a delay in the lap time. The fuzzy-PID controller in this study mimics the principle of human vehicle control as the situation-aware speed adjustment on curved paths. Consequently, it is possible to reduce the tracking error of AGV and improve its speed. Experimental results show that the Fuzzy-PID controller outperforms the PID controller in both accuracy and speed, especially the lap time of a line-following AGV is enhanced up to 28.6% with the proposed fuzzy-PID controller compared to that with the PID controller only.

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Section: Line-following Controlmentioning

confidence: 99%