A study on SLAM for indoor blimp with visual markers

The simultaneous localization and mapping (SLAM) is an essential capability for mobile robots traveling in unknown environments where globally accurate position data is not available. In this paper, we address the SLAM problem of indoor toy blimp that has no sensors such as accelerometers and gyro except a micro camera because of the weight limits. Since it is difficult to determine the exact motion models preliminarily, we assume the motion models of the blimp. The goal of this paper is to construct a 3D map of the landmarks in environment and estimate the path taken by the indoor blimp. In this paper, we use visual markers as the landmarks, since it is difficult to detect features of the landmarks. We propose the approach to SLAM using extended Kalman filter (EKF) and verify the effectiveness of this approach by the experiments.