Recent advance in Internet-of-Things (IoT) brings consumer- level smart mobile robot to our life. Indoor navigation is one of the most critical challenges for mobile robots. Existing approaches using wireless signal fingerprinting (e.g., WiFi fingerprint), computer vision techniques, require extensive war-driving of the indoor environment to collect sufficient environmental data. In this paper, we present SIGN, a lightweight, visual-tag based, indoor navigation approach that is free of indoor war-driving. The approach deploys a set of coded visual tags in the environment, and allows the robot to autonomously decide the moving direction by recognizing nearby tags and leveraging the geometry information. The proposed approach is robust to the change of the environment such as unexpected obstacles. Experiments in two indoor spaces under various scenarios show that SIGN helps the mobile robot using the off-the- shelf camera to self-navigate in indoor environment with the deployment of coded visual tags.
