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Experimental study of a quasi-optimal mobile robot switching algorithm

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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.

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