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As the risk of disaster scenes increases, the number of cases of acquiring disaster scenes information using unmanned robots is increasing. Because unmanned robots can be remotely controlled, sensors such as LiDAR and optical cameras are installed so that investigators can safely observe disaster scenes and acquire information. In particular, the information that can be acquired is different depending on the sensor characteristics, and a sensor module suitable for the purpose is being developed. Accordingly, the National Disaster Management research Institute(NDMI) also developed a investigation robot capable of acquiring information on disaster sites independently. Based on 3D point cloud data, we developed a multi-sensor module and SLAM algorithm customized to the investigation robot to collect quantitative information on the damage situation. To test the performance of the independently developed multi-sensor module, SLAM mapping was performed in a disaster building reproduced like a disaster scene, and various SLAM algorithms and distance comparison were performed. As a result, PackSLAM developed in this study showed the lowest error. In the future, to increase applicability at disaster sites, more precise experiments will be conducted by conducted by establishing a rough terrain environment.

Disasters are not easy to predict because they occur suddenly, and the scale of disasters is increasing compared to the past. Since a new type of disaster field always appears, when a disaster occurs, responders who are put into the site recognize the same risk as secondary damage and are put into the field. In this regard, the robot performs missions such as search and rescue in the initial response process at the disaster field. It is a technology with high potential to reduce damage to people and property. Most of the robots are equipped with site accessibility and monitoring through cameras and remote control, but considering the specificity of the disaster field, it is not easy to fully monitor the site with a camera sensor as the possibility of poor visibility is very high. LiDAR uses a laser to recognize the distance to a nearby object in a relatively wide range and acquires three-dimensional information, so its accuracy and precision are higher than other sensors.In this study, one multi-sensor module was manufactured by combining LiDAR and IMU sensor with a computing board for real-time monitoring so that it could be used in the field of robots. In addition, we studied how to stably mount this multi-sensor module to a robot so that it can maintain optimal accuracy at disaster field, and it is intended to be utilized as a prior research for field operation of robots equipped with sensors in the future.