Robotic Manipulator Control Algorithms for Assembly Lines

Robotic manipulators are at the forefront of industrial automation and can perform repetitive tasks such as pick and place operations with precision and efficiency. In a dynamic and evolving assembly line environment, selecting the appropriate control algorithm is important to ensure good performance. This study presents a comparison of three common control methods: Finite State Machine (FSM), Behaviour Tree (BT), and Proportional-Integral-Derivative (PID). Simulations performed on the Webots platform evaluate the main parameters of the algorithms, including completion time, accuracy, error handling capacity, and adaptability to complex scenarios. The analysis identifies the advantages and limitations of each method, providing a better understanding of their suitability for specific applications in the automation industry. The results not only inform decisions regarding the use of robotic control systems, but also provide the basis for integrating hybrid approaches and researching control technologies. Through a deep understanding of the algorithms, this research leads to the continuous development of intelligent, efficient, and effective systems.