Management of Subdivided Dynamic Indoor Environments by Autonomous Scanning System

With the development of sensing technologies, various spatial applications have been expanding into indoor spaces. For smooth spatial services, grasping indoor space information is most essential task. However, the indoor spaces is not only becoming increasingly complex, but also frequently changed than outdoor spaces. This makes it hard to provide an accurate location based service in an indoor space. This paper propose a way of managing a dynamic indoor environment by defining a multi-layered indoor model in terms of an object mobility. It allows an indoor space to be managed more elaborate and realistic than up-to-date indoor models which only consider an indoor floor plan. We firstly define a classification of indoor objects based on their characteristic to frequently change location, and propose three-layers indoor model followed by the classified objects with its mobility. Secondly, we design and implement an autonomous scanning system to understand changes of indoor situation quickly and automatically. The system is made up of a combination of IoT devices, including a programmable robot, lidar scanner and single-board computer. Finally, we demonstrate an implementation of the system with constructing the proposed model from a real indoor environment.