The evolution of Robotics lead us to aspire replacing human beings by autonomous robotic systems in the most discomforting or dangerous situations, and even to have them performing tasks that humans are incapable of. Such situations are often encountered when facing a catastrophic scenario and human rescue teams put themselves at risk in their heroic attempt to rescue victims. In nowadays society, the human life is highly valued and, consequently, Search and Rescue (SaR) missions became of extreme importance, precisely because their accomplishment can save several human lives. For that reason, rescue teams are heavily trained and, since they also comprise human beings, heavily equipped. However, they often lack technological tools to perform their mission better and in safety. The main objective of this work is to study, develop and validate a fully-integrated robotic system to eventually explore catastrophic scenarios, by providing a map of the area and the people it detected while performing its task. This is a vital information in SaR missions, and this work aims at achieving this without risking a human life in the process. To that end, a mobile robot with a Red-Blue-Green and Depth (RGB-D) sensor mounted on its top was used. Furthermore, all approaches and methods were implemented in Robot Operating System (ROS) and thoroughly analyzed to assess their accuracy and performance. However, due to hardware limitations, the results are comprehensively not optimal, but they still provide useful information that might be of great help in SaR missions. Moreover, the study and analysis of this type of sensor and its usability are valuable and are now available for upcoming developments. This work is part of the Cooperation between Human and rObotic teams in catastroPhic INcidents (CHOPIN) project, which intends to develop a support system for small-scale SaR missions in urban catastrophic scenarios by exploiting human-robot cooperation.