Dimensional Optimization of Open-Source 4-DoF Robot Arm

Abstract

The utilization of optimization methodologies to design ideal robot arm structures is gaining popularity. Topology optimization, which requires the development of robot arm morphology such as the number of joints and robot connection architecture, is a significant challenge. On the other hand, dimension optimization is concerned with selecting the appropriate size for the robot arm structure based on the known morphology. Generally, creating and optimizing the robot arm structure with a known morphology is easier, leading to a focus on the robot structure's size. This study aimed to determine the optimal optimization method for designing a robot arm that achieves specific coordinates with the best dimensions. Three optimization algorithms, namely artificial bee colony (ABC), particle swarm optimization (PSO), and cuckoo search (CS), were implemented and evaluated. Results showed that the PSO algorithm performed best with the lowest mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). Thus, the PSO algorithm was found to be the most suitable optimization algorithm for this study. This finding could lead to the development of more efficient and effective robot arm designs.