Adaptive navigation and motion planning for a mobile track robot

Localization and navigation of mobile robots precisely in an indoor environment is one of most important and challenging tasks. Navigation using conventional approaches such as Global Positioning System (GPS) and some vision based odometry are not very much effective in indoor environments. Therefore, a magnetic wheel encoding mechanism was selected in order to improve the navigational method. Also it could be with the most common localization approaches such as GPS, inertial navigation systems and laser sensors. This paper discusses a mobile robot application which navigates using magnetic wheel encoders and camera sensor. Further, the robot uses Wi-Fi to gather information and it creates intelligence to find the path dynamically. The Central control center and its main database process all available data and send the relevant control commands to the robots. Additionally, it will direct the messages between the nodes and the robot and keep robots on the correct track. The environment that the robot is moving is a pulse of black lines in white background. For the detection of the line Hough transformation has been used. It is having the capability of detecting sensor nodes using Radio-frequency identification (RFID) or Quick Response (QR) codes and taking measurements and returning to the base station avoiding obstacles communicating between nodes and the base.