PYTHON-BASED APPLICATION FOR GRAPHICAL REPRESENTATION OF THE END-EFFECTOR TRAJECTORY IN A RRR KINEMATIC ASSEMBLY

Angela-Miruna NEACȘU-PAVEL, Daniela TUNSOIU, Ileana DUGĂEȘESCU, Vlad-Cristian ENACHE, Mihaela-Elena ULMEANU, Cristian-Vasile DOICIN

Abstract


This study presents a Python-based application designed for the graphical representation of the end-effector trajectory in an RRR kinematic assembly. The research focuses on developing a python script that facilitates the analysis and visualization of robotic manipulator motion, aiding in both academic and industrial applications. The study explores one structural analysis variant using three cylindrical joints, one of which is fixed. The position kinematic equations describe the system’s motion. The Python implementation leverages key libraries, such as NumPy and Matplotlib employing an efficient computational strategy to model the kinematic behavior and generate graphical outputs. The application allows for user-coded input parameters, with predefined values tested to validate the model. The code is structured and explained, ensuring clarity and reproducibility. The system generates static trajectory graphs, providing a clear representation of the end-effector’s path and validating the theoretical kinematic model. The results demonstrate that the proposed Python-based RRR model accurately simulates the motion of a human-like arm segment, confirming the model’s effectiveness for kinematic analysis and educational applications.

Full Text:

PDF

References


Guo, X., Liu, Y., Wang, Q., Liao, X., Spherical joint actuator with backstepping sliding mode control for robotic manipulator rigid-flexible coupling system, IETE Journal of Research, 3985-4001, 2023.

Olsen, A.M., A mobility-based classification of closed kinematic chains in biomechanics and implications for motor control, Journal of Experimental Biology, 222(21), jeb195735, 2019

Begon, M., Andersen, M.S., Dumas, R., Multibody kinematics optimization for the estimation of upper and lower limb human joint kinematics: A systematized methodological review, Journal of Biomechanical Engineering, 140(3), 030801, 2018

Garant, X., Gosselin, C., Whole-body intuitive physical human-robot interaction with flexible robots using non-collocated proprioceptive sensing, IEEE Robotics and Automation Letters, 2112-2118, 2024.

Romanishin, J., Rus, D., Dynamic and repeatable modular assembly: How kinematic couplings and proprioceptive actuators simplify robotic assembly, Springer Proceedings in Advanced Robotics, 30, 308–318, 2024.

Moezzi, A., Gharib, M., Gunal, M., Design and implementation of a graphic simulator for inverse kinematics of redundant manipulators, MDPI Electronics, 9(2), 320-330, 2020.

Karbouj, B., Alshamaa, O., Al Rashwany, K., Krüger, J., Enhancing Human-Robot Collaborative Predictability through Rational Action Modeling of Robot Trajectories, CIRP Conference on Manufacturing Systems, 130, 516-523, 2024

Zhang, T., Du, Q., Yang, G., Wang, C., Chen, C.Y., Zhang C., Chen, S., Fang, Z., Assembly Configuration Representation and Kinematic Modeling for Modular Reconfigurable Robots Based on Graph Theory, MDPI, 14(3), 433, 2022

Python, https://www.python.org/downloads/

Python Libraries, https://docs.python.org/ 3/library/index.html


Refbacks

  • There are currently no refbacks.


JOURNAL INDEXED IN :