## 1 Introduction  
In the context of increasingly frequent natural and man-made disasters, the deployment of autonomous mobile robotic platforms for emergency response and search-and-rescue (SAR) operations has become a critical focus in robotics research. These systems are required to operate reliably in unstructured, dynamic, and often hazardous environments, where human intervention is limited or unsafe. To support real-world deployment, simulation environments play a pivotal role in the development, testing, and validation of robotic control architectures, localization algorithms, perception systems, and communication strategies under reproducible conditions. The integration of simulation with robotic middleware such as the Robot Operating System (ROS) has led to substantial advancements in the prototyping and verification of mobile robots. [PERSON] [1] highlights the importance of simulation for verifying robotic control applications implemented on resource-constrained hardware, such as FPGAs, emphasizing the need for reproducible and cost-efficient testbeds during early development phases. Similarly, [PERSON] [2] demonstrates the development of an outdoor mobile inverted pendulum robot, emphasizing stability control in unstructured terrain and underscoring the significance of simulation prior to physical deployment. [PERSON] [3], in their comprehensive survey on ROS2, reviews modern navigation stacks and perception pipelines, reinforcing the indispensable role of simulation for scalable, modular, and secure robotic architectures. The importance of accurate robotic modeling in Gazebo/ROS is addressed by [PERSON] [4], who provides a detailed tutorial on building custom mobile robot models, focusing on the physical and visual fidelity of simulation. [PERSON] [5] presents practical insights into mobile robot navigation using ROS and Gazebo, providing evidence of how simulation supports the iterative development of planning and control algorithms. In the field of autonomous inspection, [PERSON] [6] introduced a robotic system for radiological clutter detection, wherein simulation facilitates risk-free optimization of sensor positioning and motion strategies. [PERSON] [7] describes a ROS-based control application tested in Gazebo, designed for SAR scenarios, proving the capability of simulation to evaluate real-time teleoperation and terrain traversal. The work of [PERSON] [8] focuses on unmanned ground vehicle (UGV) modeling in ROS/Gazebo, emphasizing its use in realistic validation of vehicle dynamics, locomotion control, and mission planning. [PERSON]'s foundational RoboCup Rescue framework [9] formalized the simulation domain as a benchmark for large-scale disaster response, highlighting the role of synthetic environments in evaluating autonomous agent performance. In a more recent development, [PERSON] [10] proposed ROBOTONT, an open-source ROS-supported omnidirectional robot for education and research, where simulation forms a core part of its test pipeline. [PERSON] [11] explored simulation environments for mobile robot testing and demonstrated their necessity for early validation of real-time control loops. Similarly, [PERSON] [12] proposed a formal method for verifying ROS-based programs through actor-based modeling using the Rebeca framework, showing how simulation ensures correctness before deployment. [PERSON] [13] applied SLAM techniques to a Gazebo-simulated robot in an image-based 3D indoor model, illustrating the potential of simulation in perception-intensive scenarios. [PERSON] [14] investigates path planning algorithms for urban SAR missions, validating them within simulation environments as a precursor to deployment. [PERSON] [15] focuses on motion planning for reconfigurable mobile robots in disaster scenarios, where Gazebo simulation is used to test configuration-specific locomotion strategies. Finally, [PERSON] [16] reviews contributions to the development of SAR robots, reinforcing the importance of realistic simulation environments for prototyping complex rescue behaviors.