# Automatic Outdoor Patrol Robot Based on Sensor Fusion and Face Recognition Methods
## 1 Introduction  
Starting in 2019, with the rapid spread of Coronavirus disease (COVID-19), governments all over the world have called on people to isolate themselves at home, or even stop going to work. Therefore, when people are unable to work for various reasons, how to make automatic machinery or intelligent robots continue to work instead of human labor and let the world continue to run is currently an important goal and research issue. Robots of different types have been developed based on different requirements. Most intelligent robots integrate automation, control, electronics, mechanics, and communication technologies. The expensive intelligent robot system integrates many advanced technologies and theories such as path planning [1], image processing, obstacle avoidance technology [2], arms control [3], navigation [4], and so on. Those technologically advanced robots are usually expensive and difficult to maintain. However, a robot structure that is cheap and simple in design needs to be developed to completely replace human labor, and despite being beneficial to the whole world, this is a challenging task. After the outbreak of the pandemic, many tasks need robots that can replace humans, such as simple material transportation and environmental patrol. However, the goal is to design and develop this kind of robot that is easy to manufacture, assemble and repair, and it should be relatively cheap and practical, and although this is challenging to achieve and there is still a lot of room for improvement so far. Our lives have become troubled by the current pandemic, and when the outdoor air is no longer safe, robots are needed to replace humans in outdoor patrols. Wheeled mobile robots (WMR) are the commonly used robots in many applications. The advantages of the WMR include easy control and fast movement, therefore, the WMR was used in this study. Omnidirectional WMR has more advantages than a normal directional wheeledmobile robot, such as mode of action, easy control, and high mobility [5; 6; 7; 8]. Therefore, to design an intelligent control system that replaces human labor and make the WMR able to independently assist human patrol in an outdoor environment is the primary research motivation of this study. Since the late 1990s, many papers have been presented regarding robot outdoor patrol [9; 10; 11; 12; 13]. These studies mainly focused on navigation, obstacle avoidance, path planning, road detection, and object recognition. Intruder identification and location informing were not included. Here, we put focus on fast path planning and fast face recognition. In addition, a new function of intruder alert is added. There have been many research efforts devoted to the problem of robot path planning, such as the Dijkstra algorithm, A* algorithm, and ant algorithm [14]. For obstacle avoidance, among most studies, the majority use fuzzy controllers to control WMR [15]. For detecting obstacles, there are many kinds of sensors, such as infrared sensors, ultrasonic sensors, and laser sensors that can be used to detect obstacles. This study integrates the global navigation satellite system real-time kinematic (GNSS RTK) positioning system, laser sensor, Dijkstra algorithm, ant algorithm, fuzzy controller, CNN [16] image processing, ultrasound sensors, and webcam into an intelligent robot system to perform outdoor patrol. The laser sensor, ultrasound sensors, and fuzzy controller are applied to detect and avoid obstacles. The starting position and the goal position of the WMR in an outdoor environment are given by the GNSS RTK positioning system. The robot system uses the Dijkstra algorithm with ant algorithm to find the shortest path for patrol tasks. In the outdoors, the robots may move to an unknown environment. Therefore, a navigation system installed on the robot is particularly important, so that the robot can know the current location and check whether it reaches the destination or not. Path planning is another important issue of robot research.