The Autonomous Movement of an Omnidirectional Robot along a Calculated Trajectory

This work focuses on the difficulty of autonomously moving wheeled robots over very rough terrain where traditional navigation techniques fail. The ultimate goal of the research work is to create dynamic and mathematical models that can make the robot maneuver through complex surfaces and also avoid obstacles. Performance was tested using simulations and real-world practice in conditions such as uneven surfaces and even challenging obstacles. Key findings are that the proposed models improve the trajectory accuracy and traversal time and make the robot more robust to environmental changes. The implementation of sensor fusion technologies also enhanced the robot's environmental understanding, allowing for more effective obstacle avoidance. These models can be used in practice for applications such as search and rescue, environmental exploration, and autonomous monitoring. The study brings to our attention the models considered to leverage such applications. Our methodology consists in constructing an advanced dynamic model to reproduce wheel-terrain interactions, along with control algorithms that can react against variations in real-time terrain. The experimental design consists in testing the robot on different types of surfaces, such as rocky, sandy, and irregular terrains. The effectiveness of the proposed solutions was evaluated using metrics like trajectory accuracy, obstacle avoidance success rate, and traversal time. Integration of dynamic and mathematical model improved the obstacle avoidance ability as well as the overall navigation performance. It opens an avenue for future research, where more advanced control strategies may be implemented, such as machine learning algorithms, that would allow for even more adaptive and intelligent behavior to be exhibited from a wheeled robot. Moreover, real-time terrain mapping and human-robot interaction models can be new directions to explore additional improvements of autonomous systems in different types of complex environments. By enabling robots to navigate diverse terrains with improved precision and adaptability, this research contributes to the evolution of cutting-edge technology in wheeled robot navigation towards more versatile and dependable autonomous systems in various applications, including exploration, agriculture, and disaster response. Acknowledgements: the authors would like to express their gratitude to the Institute of Information Technologies, Russian Technological University RTU MIREA, Moscow, Russia, and Mustansiriyah University, Iraq, for their assistance and support.