Artificial intelligence and automation technology that can satisfy the ever-increasing demand for technology in industrial, commercial, medical, military and civil fields has introduced new opportunities for robotics research in past decades. In particular, the mobile robot laser navigation has always been the focus and problems in fields covering a wide spectrum of disciplines. The object of this study was to explore the mapping of mobile robot based on Hector-SLAM algorithm and the simulation experiment of the global path planning in static environments. A tracked mobile robot is designed for navigation test platform, which is mainly composed of two dimensional laser radar called Neato XV-11 laser, mobile robot chassis, PC terminal and an Android phone. The motion control commands of robot platform are published by smart phone and executed via Python code in Raspberry Pi board. After algorithm procedure for Hector SLAM are represented in depth, the map building in this way is completed on Robot Operating System (ROS) where RVIZ is run to carry out cartographic visualization. On the other hand, a new ant colony algorithm(ACO), which introduces pheromone orientation, is proposed for the issue about robot shortest path planning in static environment. The results of mapping obtained on ROS show a satisfactory level of indoor environment, which reveals the feasibility of our approach in laser navigation. Furthermore, it is proved from the simulation experiments of modified ACO algorithm that the new algorithm not only can obtain the same optimal path, but also has faster convergence speed and smaller error peak in complex static environments.
