Household Disaster Map Generation and Changing-Layout Design Simulation Using the Environmental Recognition Map of Cleaning Robots

Abstract

A household disaster map is required as a countermeasure against earthquakes, particularly in crowded, cluttered indoor spaces where evacuation is difficult. Therefore, the visualization of areas that are likely to hamper evacuation is important. This study focused on cleaning robots, which generate environmental recognition maps to control their movement. We proposed a system that detects obstacles impeding evacuation for households using an environmental recognition map generated by a cleaning robot. The map generation algorithm was based on image processing and stochastic virtual pass analysis based on a pseudo cleaning-robot model. Image processing involving the binarization process was conducted to identify the interior and exterior areas of a room. Stochastic virtual pass analysis was performed to track the coordinates (i.e., virtual pass of the robot model) inside the room. Furthermore, the proposed system was tested in a laboratory, and the application of the changing-layout design simulation was considered.