A Composed Global Localization System for Service Robot in Intelligent Space Based on Particle Filter Algorithm and WIFI Fingerprint Localization

With the combination of intelligent space technology and ROS (robot operating system) service robot, a composed global localization system for service robot based on Monte Carlo particle filter algorithm and WIFI fingerprint localization is presented. This system can solve the global localization problem in which the initial pose of service robot is unknown and the robot pose is determined according to sensor information. In the composed localization method, robot rough localization is realized firstly using the WIFI fingerprint localization based on BP (backpropagation) neural network under the support of intelligent space technology, and the estimated position and estimation error are sent to the ROS service robot. Based on the rough localization result, Monte Carlo particle filter algorithm is adopted to get precise position of the ROS robot. The experiment results show that the proposed system can realize zero-configuration and loose coupling between ROS service robot and intelligent space, improve precision of global localization of the ROS service robot effectively, and reduce the iteration time.