Experimental study of a quasi-optimal mobile robot switching algorithm

   Omnidirectional mobile platforms, known for their exceptional maneuverability in confined spaces, often encounter not only energy efficiency challenges due to the design of roller-bearing wheels but also operational limitations in real-world environments such as height differences and uneven terrain. To overcome these limitations, it is necessary to enable switching between omnidirectional and conventional driving modes through adaptive motion mode switching. This approach combines the maneuverability required for navigation in tight spaces with improved off-road capability and energy efficiency on uneven surfaces and slopes. This study proposes an algorithm for adaptive motion mode switching, providing transitions from an omnidirectional to a classical kinematic scheme and back via a specially developed compact switching mechanism. To achieve this, enhanced kinematic, dynamic, and energy models were utilized in combination with laboratory experiments conducted on a reconfigurable platform. The proposed improvements make it possible to perform a simple and rapid transition between kinematic configurations using the compact switching mechanism. Experimental studies were carried out under laboratory conditions on a flat concrete surface where the robot followed a closed trajectory. During the experiments, energy consumption and trajectory-tracking errors were recorded for holonomic, nonholonomic, and reconfigurable motion modes. Comparative analysis demonstrated that the proposed switching algorithm reduces energy consumption by an average of 8 % while maintaining maneuverability. For larger robots whose total mass significantly exceeds that of the reconfiguration mechanism energy savings in real-world scenarios can be even greater due to the system ability to optimize energy usage and select the most efficient configuration for different trajectory segments. The system retains high maneuverability and ensures efficient navigation in complex environments. The presented algorithm enables the platform to achieve a crucial balance between mobility, efficiency, and control accuracy. This opens the possibility for the practical implementation of reconfigurable robots in real-world service applications. The obtained results have practical significance for the design of adaptive mechanical and control systems that enhance the operational flexibility of mobile platforms under resource-constrained conditions.

1. Chen W., Wu P., Gong Y., Zhang Z., Wang K. The role of energy consumption in robotic mobile fulfillment systems: Performance evaluation and operating policies with dynamic priority. Omega, 2025, vol. 130, pp. 103168. doi: 10.1016/j.omega.2024.103168

2. Kim T., Kang G., Lee D., Shim D.H. Development of an indoor delivery mobile robot for a multi-floor environment. IEEE Access, 2024, vol. 12, pp. 45202–45215. doi: 10.1109/access.2024.3381489

3. Kebede G., Gelaw A., Andualem H., Hailu A.T. Review of the characteristics of mobile robots for health care application. International Journal of Intelligent Robotics and Applications, 2024, vol 8, no. 2, pp. 480–502. doi: 10.1007/s41315-024-00324-3

4. Giurgiu T., Bârsan G., Virca I., Pupăză C. Mecanum wheeled platforms for special applications. International conference KNOWLEDGE-BASED ORGANIZATION, 2022, vol. 28, no. 3, pp. 44–51. doi: 10.2478/kbo-2022-0086

5. Zhewen Z., Hongliu Y., Chengjia W., Pu H., Jiangui W. A comprehensive study on mecanum wheel-based mobility and suspension solutions for intelligent nursing wheelchairs. Scientific Reports, 2024, vol. 14, no. 1, pp. 20644. doi: 10.1038/s41598-024-71459-3

6. Qian J., Zi B., Wang D., Ma Y., Zhang D. The design and development of an omni-directional mobile robot oriented to an intelligent manufacturing system. Sensors, 2017, vol. 17, no. 9, pp. 2073. doi: 10.3390/s17092073

7. Vestman R. A Comparative Study of Omnidirectional and Differential Drive Systems for Mobile Manipulator Robots : A Performance Review of Strengths and Weaknesses. Dissertation. 2023, 60 p.

8. Minh D.N., Do Quang H., Phuong N.D., Manh T.N., Bui D.N. An adaptive fuzzy dynamic surface control tracking algorithm for mecanum wheeled mobile robot. International Journal of Mechanical Engineering and Robotics Research, 2023, vol. 12, no. 6, pp. 354–361. doi: 10.18178/ijmerr.12.6.354-361

9. Yang X., Hu Y., Gao H., Ding K., Li Z., Zhu P., Sun Y., Liu C. Risk-aware non-myopic motion planner for large-scale robotic swarm using cvar constraints. Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 5784–5790. doi: 10.1109/iros58592.2024.10802191

10. Zhu K., Zhang T. Deep reinforcement learning based mobile robot navigation : a review. Tsinghua Science and Technology, 2021, vol. 26, no. 5, pp. 674–691. doi: 10.26599/tst.2021.9010012

11. Zakharov D.N., Iaremenko A.M., Kurovskii D.M., Kurovskii A.M., Borisov O.I., Zhang B. Development of a mobile reconfigurable mecanum robot with a locking device of rollers. Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 3553–3558. doi: 10.1109/iros58592.2024.10801549

12. Abd Mutalib M.A., Azlan N.Z. Prototype development of mecanum wheels mobile robot : a review. Applied Research and Smart Technology (ARSTech), 2020, vol. 1, no. 2, pp. 71–82. doi: 10.23917/arstech.v1i2.39

13. Xie L., Herberger W., Xu W., Stol K.A. Experimental validation of energy consumption model for the four-wheeled omnidirectional mecanum robots for energy-optimal motion control. Proc. of the IEEE 14^th International Workshop on Advanced Motion Control (AMC), 2016, pp. 565–572. doi: 10.1109/amc.2016.7496410

14. Zakharov D.N., Kurovskii D.M., Kurovskii A.M., Zhivitskii A.Y., Borisov O.I., Fakhro K., Pyrkin AA. Experimental study of trajectory control algorithms under incomplete information on parameters and state variables of a nonlinear model of mobile robot motion. Proc. of the 10^th International Conference on Control, Decision and Information Technologies (CoDIT), 2024, pp. 1584–1588. doi: 10.1109/codit62066.2024.10708441