Investigation of various forms of nonlinearities in differential drive wheel mobile robots and its influence on its kinematic model

Abstract

The study of wheeled mobile robot Kinema􀆟c has long been a cornerstone of robo􀆟cs research, as it underpins the fundamental understanding of how these machines navigate and interact with their environments. The influence of nonlineari􀆟es in differen􀆟ally powered wheeled mobile robots is a crucial issue that is o􀅌en overlooked. The different nonlineari􀆟es observed in such systems are examined in this study abstract together with their significant impacts on robot Kinema􀆟c. Differen􀆟ally driven wheeled mobile robots, characterized by two independently driven wheels, offer simplicity and maneuverability, making them prevalent in various applica􀆟ons. However, there are major difficul􀆟es due to the intrinsic nonlineari􀆟es in their mo􀆟on dynamics. Nonlineari􀆟es arise from wheel slippage, backlash in gear, varia􀆟ons in terrain, and mechanical imperfec􀆟ons, among other factors. These nonlineari􀆟es can result in devia􀆟ons between the desired and actual robot trajectories. For precise mo􀆟on control, localiza􀆟on, and path planning, it is crucial to understand these nonlineari􀆟es. In this abstract, we discuss the common sources of nonlineari􀆟es in differen􀆟ally driven wheeled mobile robots and their effects on kinema􀆟c models. We explore how these nonlineari􀆟es can lead to wheel slippage, odometry errors, and backlash in the motor gear and devia􀆟ons in the robot's es􀆟mated pose. We also explore methods for modelling and reducing these nonlinear impacts. This comprises the applica􀆟on of sophis􀆟cated mo􀆟on planning algorithms, adap􀆟ve control techniques, and sensor fusion. By addressing these challenges, we aim to improve the overall performance and reliability of differen􀆟ally driven wheeled mobile robots in real-world applica􀆟ons. This abstract's conclusion emphasizes the need of taking nonlinearities into account while designing differentially powered wheeled mobile robots. Understanding and addressing these non-idealities are crucial steps toward advancing the capabilities and robustness of these robots in diverse environments, paving the way for their continued integration into various fields, such as autonomous navigation, logistics, and exploration.