## 1 Introduction  
In today's rapidly advancing field of robotics, the development of mobile platforms with interchangeable wheels has gained significant attention. These platforms offer increased flexibility and adaptability, allowing for efficient navigation on various terrains and in different operational scenarios [1, 2, 3, 4]. Furthermore, the ability to interchange between conventional wheels and Mecanum wheels provides additional maneuverability and enhances the platform's functionality [5, 6, 7, 8]. In this paper, we aim to develop a dynamic model that accurately captures the resistive forces experienced by such mobile platforms, considering factors such as wheel profiles, mass, static forces, inertia, and most importantly frictional forces. Dynamic modeling of mobile platforms is a crucial aspect of their design and control [9, 10]. It helps engineers understand the behavior and performance of the platform under different operating conditions. Several researchers have explored the kinematic and dynamic properties of wheeled mobile platforms, analyzed the kinematic properties of wheeled mobile robots, and identified rolling and sliding constraints as significant limitations to the motion of the platform wheels [11, 12, 13, 14, 15, 16, 17, 18]. In [15], [PERSON] expanded on this work by describing the singular and heterogeneous types of mobile robots based on Mecanum wheels and Caster wheels. In [18, 19, 20],[PERSON] and [PERSON] established a kinematics model for omnidirectional mobile robots under sliding conditions. Similarly, [PERSON] and [PERSON] focused on the steering motion of a Mecanum-wheeled omnidirectional mobile platform. They established a control system model and dynamic model using MATLAB R2016 software [17; 21; 22]. In [23], the authors focused on developing a fault detection method for Markov Jump systems using fuzzy models. It specifically addresses scenarios where transition probabilities are only partially known, aiming to improve fault detection accuracy and reliability in such systems. In [24], [PERSON] involves the analysis and study of differentiable fuzzy logic operators to explore mathematical properties, optimization techniques, and the applications of such operators in various domains, such as machine learning and control systems. In [25], [PERSON] presents a method for autonomously switching the gait of a hexapod walking robot to navigate various terrains in a Mars-like environment. It involves experimental validation and testing of the proposed method to demonstrate its effectiveness in real-world scenarios. In [26], [PERSON] explores the integration of artificial intelligence, gesture interaction, and deep learning methods in musical perception education. It involves the development of a system or platform that utilizes these technologies to enhance learning experiences in the field of musical perception. Also, in [27], the research is focused on developing control strategies for a bionic mantis shrimp robot to track targets. It involves the implementation of closed-loop central pattern generators, inspired by biological systems, to achieve precise and agile target tracking capabilities. However, while these studies have made significant contributions to the understanding of mobile platform dynamics, they have primarily focused on kinematic modeling and have not fully considered the dynamic model considering resistive frictional forces experienced by the platform. The lack of comprehensive models incorporating resistive forces is addressed in this study. The objective of this study is to develop a dynamic model for mobile platforms with interchangeable wheels, including both conventional and Mecanum wheels. This model will take into account not only the mass and static forces but also the inertia of the robot and moving wheels, as well as the frictional forces acting on the platform. The dynamic model will be constructed in Simscape Simulink, a platform for simulating physical systems. First, a 3D model of the mobile platform will be created in SolidWorks.