With the growing demand for location-based services such as indoor navigation, robot control and object tracking, indoor positioning technology has attracted increasing attention from both academia and industry. For outdoor environments, the Global Positioning System (GPS) provides real-time positioning services based on satellites and is widely used in airplanes, automobiles and portable devices. However, it cannot realize efficient positioning in indoor environments because satellite signals will be extremely attenuated and interrupted by indoor obstacles. Currently, wireless technologies, including Bluetooth and WiFi, are widely applied to indoor positioning systems. However, these technologies can only achieve meter-level accuracy and are potentially vulnerable to malicious activiti...[ Read more ]

With the growing demand for location-based services such as indoor navigation, robot control and object tracking, indoor positioning technology has attracted increasing attention from both academia and industry. For outdoor environments, the Global Positioning System (GPS) provides real-time positioning services based on satellites and is widely used in airplanes, automobiles and portable devices. However, it cannot realize efficient positioning in indoor environments because satellite signals will be extremely attenuated and interrupted by indoor obstacles. Currently, wireless technologies, including Bluetooth and WiFi, are widely applied to indoor positioning systems. However, these technologies can only achieve meter-level accuracy and are potentially vulnerable to malicious activities. Visible light positioning (VLP) technology can solve these problems, with multiple advantages including centimeter-level accuracy, compatibility with existing lighting infrastructure, low cost and insusceptibility to electromagnetic interference. Therefore, VLP systems are very competitive to provide indoor positioning service. In this thesis, a high-accuracy VLP system is proposed, based on which robotic navigation and map construction is also achieved. The design and implementation of the system is divided into three parts.

In the first part, an image sensor-based single-LED VLP system is proposed. The additional positioning error caused by tilted receiver camera is corrected by the rotation angles estimated by the inertial sensors. The proposed VLP system can also provide positioning services even when an incomplete LED image is captured by the camera.

In the second part, a VLP-based mobile robot experiment platform is built. The proposed platform consists of two parts: intelligent lighting and image sensor-based VLP light tracking. Smart LEDs are used as the access points of the VLP system and are modulated with digital IDs containing the information of the LEDs’ world coordinates. Therefore, the proposed positioning system is scalable, with no maximum scale limit. The camera mounted on robot will capture the images of LEDs and use ID recognition algorithm to identify the IDs then get the position with geometric feature-based image processing algorithm. Based on the proposed robot positioning and navigation system, a panorama creation method is proposed which can generate a panorama at any target point using a robot mounted with an ordinary USB camera.

In the final part, an autonomous map construction method using VLP landmarks and Simultaneous Localization and Mapping (SLAM). A layout map of the environment to be perceived is calibrated by a robot tracking at least two landmarks mounted in the venue. At the same time, the robot's position on the occupancy grid map generated by SLAM is recorded. A map transformation method is then performed to align the orientation of the two maps and to calibrate the scale of the layout map to agree with that of the sensor map. After the calibration, the semantic information on the layout map remains and the accuracy is improved.