Design and Experiment of a Greenhouse Autonomous Following Robot Based on LQR–Pure Pursuit

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Bibliografiset tiedot
Julkaisussa:Agriculture vol. 15, no. 15 (2025), p. 1615-1646
Päätekijä: Hu, Yibin
Muut tekijät: Jieyu, Xian, Xiao Maohua, Cheng Qianzhe, Chen, Tai, Zhu Yejun, Geng Guosheng
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MDPI AG
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022 |a 2077-0472 
024 7 |a 10.3390/agriculture15151615  |2 doi 
035 |a 3239016043 
045 2 |b d20250101  |b d20251231 
084 |a 231331  |2 nlm 
100 1 |a Hu, Yibin 
245 1 |a Design and Experiment of a Greenhouse Autonomous Following Robot Based on LQR–Pure Pursuit 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Accurate path tracking is crucial for greenhouse robots operating in complex environments. However, traditional curve tracking algorithms suffer from low tracking accuracy and large tracking errors. This study aim to develop a high precision greenhouse autonomous following robot, use ANSYS Workbench 19.2 to perform stress and deformation analysis on the robot, then propose a path tracking method based on Linear Quadratic Regulator (LQR) to optimize the pure tracking to ensure high precision curved path tracking for curved tracking, finally perform a comparative simulation analysis in MATLAB R2024a. The structural analysis shows that the maximum equivalent stress is 196 MPa and the maximum deformation is 1.73 mm under a load of 600 kg, which are within the yield limit of 45 steel. Simulation results demonstrate that at a speed of 2 m/s, the conventional Pure Pursuit algorithm incurs a maximum lateral error of 0.3418 m and a heading error of 0.2669 rad under high curvature conditions. By contrast, the LQR–Pure Pursuit algorithm reduces the peak lateral error to 0.0904 m and confines the heading error to approximately 0.0217 rad. Experimental validation yielded an RMSE of 0.018 m for lateral error and 0.016 m for heading error. These findings confirm that the designed robot can sustain its payload under most operating scenarios and that the proposed tracking strategy effectively suppresses deviations and improves path-following accuracy. 
651 4 |a Shenzhen China 
651 4 |a China 
653 |a Humidity 
653 |a Agricultural production 
653 |a Algorithms 
653 |a Deformation 
653 |a Structural analysis 
653 |a Robots 
653 |a Path tracking 
653 |a Motion control 
653 |a Crops 
653 |a Deformation analysis 
653 |a Pursuit tracking 
653 |a Localization 
653 |a Tracking errors 
653 |a Simulation analysis 
653 |a Energy consumption 
653 |a Radiation 
653 |a Greenhouses 
653 |a Efficiency 
653 |a Accuracy 
653 |a Agriculture 
653 |a Linear quadratic regulator 
653 |a Control algorithms 
653 |a Planning 
653 |a Root-mean-square errors 
653 |a Sensors 
653 |a Environmental 
700 1 |a Jieyu, Xian 
700 1 |a Xiao Maohua 
700 1 |a Cheng Qianzhe 
700 1 |a Chen, Tai 
700 1 |a Zhu Yejun 
700 1 |a Geng Guosheng 
773 0 |t Agriculture  |g vol. 15, no. 15 (2025), p. 1615-1646 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3239016043/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3239016043/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3239016043/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch