## 3 Results and Discussion  
The results written below are simulated in the WebBotes virtual environment. This software is a physically based simulation environment that can be used to run scenarios from a number of robotic agents in custom-built environments. In this instance, a Pioneer 3D-X was replicated. The Pioneer 3D-X is a mobile robot platform designed for autonomous navigation and mapping tasks in indoor environments. It is equipped with a range of sensors, including a 2D laser scanner, a stereo vision camera system, and an inertial measurement unit, which enable it to accurately perceive its surroundings and generate a 3D map of the environment. The robot is powered by a high-performance computing system that enables it to perform real-time data processing and decision making, and it is capable of navigating through complex environments with obstacles and dynamic changes. The following results are categorised into three sets, each measuring the pose estimation of a single agent. An initial image is provided below to establish the ground truth of the measured agent and to provide a measurable baseline. All agents employ the approach outlined in this paper. The first set of results shows a single agent using a 3D depth camera. The second set presents the results of a single agent using LiDAR. Finally, the third set of results showcases the same LiDAR agent, but this time utilising the 3D data from the other agent. Figure 22 shows the ground truth of the measured agent. Figures 23 and 24 are showing the single 3D agent. Based on Figure 25, it is evident that the error in the pose estimate escalated rapidly and almost exponentially. Although this error curve may decrease slightly over time, it does not align with our expectations. This single agent is operating in a simulated and relatively sparse environment, which makes it challenging to localise accurately. Figure 21: Figure for alignment between 2D and 3D agents. Figure 23: Data of 3D agents position estimation. Figure 24: Data showing error over time for 3D Agent. Figure 22: Data of ground truth of the measured agent  
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