Structural Optimization of 4-DOF Agricultural Robot Arm

被引:1
|
作者
Zakey, Nurul Emylia Natasya Ahmad [1 ]
Zaman, Mohd Hairi Mohd [1 ]
Ibrahim, Mohd Faisal [1 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Dept Elect Elect & Syst Engn, Bangi, Malaysia
来源
JURNAL KEJURUTERAAN | 2024年 / 36卷 / 03期
关键词
Agricultural; Structural optimization; Robot manipulator; Artificial bee colony; Particle swarm optimization; Forward kinematic;
D O I
10.17576/jkukm-2024-36(3)-23
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The shortage of human labor is increasing; thus, more agricultural machinery and equipment are expected to enter the agricultural sector. One of the agricultural machinery widely studied nowadays involves robot arms. Therefore, developing robot arms is a hot issue in this field. The ideal structure of the robot arm with optimal length is currently gaining popularity and being used in many sectors, such as manufacturing and agriculture. This is closely related to the dynamic structure of agricultural areas. Therefore, this study uses the forward kinematic modeling method to design an optimal robot arm to achieve a specific coordinate in a dynamic environment. The robot in this study arm mimics the boom and arm installed on a tractor. The forward kinematic problem in this study is defined using the Denavit-Hartenberg (DH) convention method. The DH convention is commonly used to solve kinematic analysis problems of a robot arm. Simulation of kinematic modeling is performed using MATLAB software. This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. The comparison between artificial bee colony (ABC) and particle swarm optimization (PSO) is studied. At the end of the study, the best algorithm was selected for the robot arm design with a four- degree-of-freedom (4-DOF). The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.
引用
收藏
页码:1127 / 1134
页数:8
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