## 3 Overview of the Solution  
The presented simulator allows researchers to quickly bootstrap a lunar environment, to develop and test algorithms for autonomous rovers. This technology has the potential to significantly accelerate the development of lunar exploration systems by allowing researchers to generate synthetic data and efficiently test rover algorithms in a controlled environment. This is particularly relevant given the substantial costs and logistical complexities associated with real-world lunar missions or even analogue missions. Visual data also empower researchers to explore the potential impact of external factors on algorithmic performance. For instance, lighting conditions, visibility limitations, and variations in terra-rain textures can all influence the outcomes of the rover's perception and decision making algorithms. By manipulating these visual variables in the simulator, researchers can assess  
Figure 2: Example images from synthetic lunar and planetary environments. The proposed LunarSim (**top** row) generates more realistic images than those available in [36] (**middle** row) or [33] (**bottom** row) while also enabling ROS-compatible control and extensive hardware support, making it a viable solution for a broader range of applications than State-of-the-Art simulators. the robustness of their algorithms and devise strategies to mitigate the adverse effects of real-world uncertainties. The block diagram of the complete system is shown in Figure 3.  
To address concerns about the theoretical underpinning of the simulated lunar environment, our approach relies on the meticulous integration of empirical data and established lunar knowledge. The simulator's fidelity is achieved by incorporating satellite imagery and images from lunar missions. Moreover, to establish the simulator's theoretical validity, we have aligned its parameters with known lunar properties, such as gravitational conditions, illumination angles, and illumination temperature. The rover's physical attributes, including its size, weight, speed, and sensor capabilities, have been derived from real-world technologies and devices. These parameters were not only inspired by existing technology but also tuned to ensure that the use of the simulated rover would mirror sensors in the real world. This integration of established knowledge not only reinforces the simulator's authenticity but also provides a foundation for its representation of the lunar surface. The Unity real-time development platform was selected as a simulation engine. The engine enables realistic scene rendering and accurate physical simulation out of the box. An artificial lunar landscape was built, using proprietary assets such as textures and models, as the game engine facilitates the use and import of models, objects, textures, and material data from various sources, both free and nonfree. The terrain contains some craters, hills, and flatlands, forming an area 950 \(\times\) 950 m large. It is highly inspired by the Moon's surface but does not imitate any true part of the Moon. Similarly, rock models were created, textured, and manually placed in the terrain. A blending strategy was employed for the albedo (colour) maps and normal textures, making the integration of the lunar soil and other objects more natural. Additional post-processing effects, such as colour grading, ambient occlusion, contact shadows, and screen space reflections, were used, to further improve photorealism. It is worth noting that the scene's lighting can also be easily controlled, to simulate realistic effects like shadows, glare, lens flares, etc. The physical forces of the lunar environment are simulated and controlled by the NVIDIA PhysX engine [37]. The ability to freely model the lighting conditions is an important step in providing the necessary level of realism. Moreover, the ability to change the lighting-related parameters of the atmosphere and materials enables simulation in a range of realistic conditions, improving the robustness of the resulting solution.