Real-time Mapping of Multi-Floor Buildings Using Elevators

Sahar Leisiazar, Mohammad Mahdavian, Edward J. Park, Mo Chen

Abstract: This paper discusses the creation of a map of multi-floor buildings using elevators in autonomous and manual driving modes. Two disadvantages of existing Simultaneous Localization And Mapping (SLAM) algorithms are inability to detect elevation change and drift inside reflective environments such as many modern elevators. Therefore, we integrate the LeGO-LOAM SLAM algorithm with air pressure data collected by a barometric pressure sensor to create a map of a multi-story building in real-time without losing track of robot’s movement inside an elevator. To achieve this, we developed an elevator detection module to detect elevators using a depth camera and locate them in floor maps. In autonomous driving mode, after exploring and mapping one floor, the robot autonomously navigates to the detected elevator, takes it to another floor, and starts mapping the new floor without losing track of the robot’s position despite sudden changes in the environment during this process. The manual driving mode is subsequently added to evaluate the performance of the system and the accuracy of the generated map. The experimental results show that the proposed algorithm is capable of mapping multiple floors autonomously and manually with minimal drift.