A corner and straight line matching localization method for family indoor monitor mobile robot

The hybrid localization method of straight line matching, corner matching and odometry is proposed to resolve the difficult localization problems of mobile robot operating in family indoor environment. Localization of robot is a challenge problem which involves of determining robot positioning relative to objects in the environment. The system is implemented using National Instrument Labview platform to gain satisfied real time performance with CompactRIO support. Robot detects environment using a 2D laser range finder with TCP/IP protocol. Line feature extraction process include area divided, iterative end point fit (IEPF) and a least square technique is introduced. Based on line feature, straight lines and corners as geometry features are obtained. The detected straight lines and corners are matched with the global straight lines and corners to obtain the robot position/orientation value. The odometry localization algorithm, straight line localization algorithm and corner localization algorithm are discussed. Different weight values are distributed to straight lines, corner and odometry according to the error model. As a result stable localization is achieved with position and orientation resolution as 50 mm, 5 degree. A good performance for the method is also achieved with cycle time as 120 ms. Experiment shows the effectiveness of the hybrid localization method.