<p>This paper presents the design and implementation of a physics-inspired interval type-2 fuzzy logic (IT2FL) control system and an optimized kinematics model for intelligent robotic mobile manipulators equipped with a robotic arm and a mobile platform. The robotic system consists of a six-degree-of-freedom (DOF) arm mounted on a four-DOF Mecanum mobile platform, resulting in a 10-DOF redundant configuration. The forward kinematics is first derived using a geometrical approach to establish the mapping between the configuration space and the workspace. To determine the optimal inverse kinematics solutions, the physics-inspired simulated annealing (SA) algorithm is incorporated with the Newton–Raphson method. Taking the optimized kinematics analysis, a SA-based interval type-2 fuzzy logic proportional–integral–derivative (SA-IT2FL-PID) control scheme is proposed to address the intelligent control challenges of the mobile manipulator system. In this study, the SA physics-inspired algorithm is employed not only to optimally compute the inverse kinematics configuration but also to optimize the fuzzy structure of the IT2FL-PID controllers for the 10-DOF robotic mobile manipulators. The proposed SA-IT2FL-PID physics-based redundant control method utilizes the heuristic SA process for automatic tuning of PID control gains. To validate the effectiveness of the proposed methods, an experimental robotic mobile manipulator is developed, consisting of a 6-DOF collaborative robot arm and a customized 4-DOF Mecanum platform. Numerical simulations, comparative analyses, and real-world experiments are conducted to demonstrate the efficacy, applicability, and advantages of the SA-based kinematics modeling and the self-tuning SA-IT2FL-PID control strategy for robotic mobile manipulators.</p>