Multidisciplinary Journal of Science and Technology

PARAMETERS FOR MOBILE ROBOT KINEMATIC MODEL DEVELOPMENT DETERMINATION

Heorhii Borysov

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Svitlana Maksymova

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Keywords: Mobile robot, Kinematic model, Kinematic characteristics, Navigation, Path development

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Abstract

The problem of creating a mobile robot kinematic model is due to its necessity for controlling the robot. In this case, understanding the design features of the robot, as well as its movers, is of great importance. The primary task is to select the necessary parameters to create a kinematic model. The article discusses the design of the robot being developed. And a choice of parameters is proposed for creating a kinematic model of this mobile robot.

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References

Lai, R., & et al. (2018). Review of research on the key technologies, application fields and development trends of intelligent robots. In Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Springer International Publishing, 2(11), 449-458.

Attar, H., & et al.. (2022). Zoomorphic mobile robot development for vertical movement based on the geometrical family caterpillar. Computational Intelligence and Neuroscience, 2022.

Lyashenko, V., & Sotnik, S. (2020). Analysis of Basic Principles for Sensor System Design Process Mobile Robots. Journal La Multiapp, 1(4), 1-6.

Nevliudov, I., & et al.. (2020). Development of a cyber design modeling declarative Language for cyber physical production systems. J. Math. Comput. Sci., 11(1), 520-542.

Baker, J. H., & et al.. (2021). Some interesting features of semantic model in Robotic Science. SSRG International Journal of Engineering Trends and Technology, 69(7), 38-44.

Abu-Jassar, A. T., & et al.. (2021). Some Features of Classifiers Implementation for Object Recognition in Specialized Computer systems. TEM Journal: Technology, Education, Management, Informatics, 10(4), 1645-1654.

Al-Sharo, Y. M., & et al.. (2021). Neural Networks As A Tool For Pattern Recognition of Fasteners. International Journal of Engineering Trends and Technology, 69(10), 151-160.

Sotnik, S., & et al.. (2020). Some features of route planning as the basis in a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(5), 2074-2079.

Ahmad, M. A., & et al.. (2020). Features of the construction and control of the navigation system of a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(4), 1445-1449.

Sotnik, S., & Lyashenko, V. (2022). Prospects for Introduction of Robotics in Service. Prospects, 6(5), 4-9.

Matarneh R., & et al. (2018). Voice Control for Flexible Medicine Robot. International Journal of Computer Trends and Technology (IJCTT), 55(1), 1-5.

I. Nevliudov, & et al. (2023). Mobile Robot Navigation System Based on Ultrasonic Sensors. In 2023 IEEE XXVIII International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), Tbilisi, Georgia, 247-251.

Basiuk, V., & et al. (2023). Mobile Robot Position Determining Using Odometry Method. Multidisciplinary Journal of Science and Technology, 3(3), 227-234.

Yevsieiev V., & et al. (2022). Software Implementation Concept Development for the Mobile Robot Control System on ESP-32CAM. In Current issues of science, prospects and challenges: collection of scientific papers «SCIENTIA» with Proceedings of the II International Scientific and Theoretical Conference, Sydney, Australia: European Scientific Platform, 2, 54-56

Yevsieiev, V., & et al. (2022). A robotic prosthetic a control system and a structural diagram development. Collection of Scientific Papers «ΛΌГOΣ», Zurich, Switzerland, 113–114.

Matarneh R., & et al. (2017). Building Robot Voice Control Training Methodology Using Artificial Neural Net. International Journal of Civil Engineering and Technology, 8(10), 523–532.

Maksymova S., & et al. (2017). Voice Control for an Industrial Robot as a Combination of Various Robotic Assembly Process Models. Journal of Computer and Communication, 5, 1-15.

Huang, X., & et al. (2021). Kinematic modeling and control of variable curvature soft continuum robots. IEEE/ASME Transactions on Mechatronics, 26(6), 3175-3185.

Rijalusalam, D. U., & Iswanto, I. (2021). Implementation kinematics modeling and odometry of four omni wheel mobile robot on the trajectory planning and motion control based microcontroller. Journal of Robotics and Control (JRC), 2(5), 448-455.

Jiang, H., & et al. (2019). Design and kinematic modeling of a passively-actively transformable mobile robot. Mechanism and Machine Theory, 142, 103591.

Lafmejani, A. S., & et al. (2020). Kinematic modeling and trajectory tracking control of an octopus-inspired hyper-redundant robot. IEEE Robotics and Automation Letters, 5(2), 3460-3467.

Abbatematteo, B., Tellex, S., & Konidaris, G. (2019). Learning to generalize kinematic models to novel objects. In Proceedings of the 3rd Conference on Robot Learning.

Li, Y., & et al. (2019). Kinematic modeling of a combined system of multiple mecanum-wheeled robots with velocity compensation. Sensors, 20(1), 75.

Jin, S., & et al. (2019). Kinematic model and real-time path generator for a wire-driven surgical robot arm with articulated joint structure. Applied Sciences, 9(19), 4114.

Rabiee, S., & Biswas, J. (2019). A friction-based kinematic model for skid-steer wheeled mobile robots. In 2019 International Conference on Robotics and Automation (ICRA), IEEE, 8563-8569.

Toquica, J. S., & et al. (2021). An analytical and a Deep Learning model for solving the inverse kinematic problem of an industrial parallel robot. Computers & Industrial Engineering, 151, 106682.

Zhang, Z., & et al. (2022). Kinematic calibration of cable-driven parallel robots considering the pulley kinematics. Mechanism and Machine Theory, 169, 104648.

Cursi, F., & et al. (2020). Adaptive kinematic modelling for multiobjective control of a redundant surgical robotic tool. Robotics, 9(3), 68.

Kana, S., & et al. (2022). Fast kinematic re-calibration for industrial robot arms. Sensors, 22(6), 2295.