Mechatronical approach to investigations of rescue operations

World faced a number of natural and man-triggered catastrophic disasters during the last decade, originated by earthquakes and terrorist attacks. Hence, term “rescue operations” and “Urban Search and Rescue (USAR)” gained new sense. Time of rescue teams to find people buried in ruins is too short (about 48 hours). Analysis shows that all world centres for robotics, autonomous systems and artificial intelligence work on problems of design and control of rescue devices and processing of inflowing sensor data. This paper presents a mechatronical approach to investigations of rescue operations. This approach consists of some steps: USAR constraints on robots and sensors; USAR requirements for mobility and sensing; new strategy for victim location in rescue operations; Human-Robot Interaction (HRI) in rescue operations. The USAR domain presents extremely difficult environmental constrains on both the robot designer and programmer. This section examines the constraints imposed in terms of hardware and software issues. When designing a robot for the purpose of USAR, these aspects must be strongly considered and implemented The main goal for mobility is research and development of technologies to build mobile robots with high degree of mobility. Sensors for USAR robots fall into two broad categories: control of the robot and victim identification. The victim identification strategy has two components: firstly the sensor data is processed to produce signs of life; secondly these signs of life are mapped to an occupancy grid to localize different victims with respect to the main map of environment. Search and rescue operations is a near-ideal robots application for studying Human-Robot Interaction /HRI/. A domain theory of search and rescue activity consists of two parts: (1) a workflow model identifying the major tasks, actions and roles in robot assisted search and rescue and (2) a general information flow model of how data from the robot is- fused by various team members into information and knowledge.