Research On Mobile Robots Navigation Based On Wireless Sensor Networks

Since rescue robots can replace people to get to dangerous fields, such as, fires and mines, it attracts broad attention from domestic and overseas research institutes. Traditional rescue robots, limited by the short control distance, small range of perception and inaccurate positioning accuracy, had great difficulties in their application. This thesis, combing mobile robots and wireless sensor networks (WSN), studies mobile robot navigation system based on wireless sensor network. The research has positive practical significance and scientific value.This thesis designs and implements multi-hop wireless sensor network communication links to tackle traditional short range communication problem. Through the WSN’s self-construction function, it can form a much larger multi-hop communication chain, which can meet the needs of the rescue tasks of complex environments. At the same time, the wireless sensor network can carry some sensors, such as temperature, humidity, gas concentration, and can perceive the real time environment information, for the operators to plan the rescue mission. Mobility, robot’s strong computation ability and the communication distance, distributed computation of wireless sensor network combined can significantly improve the efficiency of executing a rescue mission.To enhance the capabilities of the mobile robot motion control, this thesis introduces ROS (Robot Operating System) design and build a mobile robot platform. Hardware uses the iRobot differential drive chassis and UTM 30LX laser radar. As using only dead reckoning odometer-based approach in mathematical models and analysis can lead a large error and the error covariance monotonically, therefore, environmental features to correct the position of robots is used, by continuously iterative using Extend Kalman filter to stabilize the system and error covariance does not change by time any more. On this basis of mapping, this thesis proposed a simultaneous location and mapping algorithm based on Hector SLAM. Laser data matching system is used to locate the robot. Local map is connected to a global map. Experimental results show that the algorithm is relatively robust and can achieve high accuracy in rough terrain.For indoor mobile robot navigation, an algorithm based on wireless sensor network is proposed in the thesis. The WSN nodes with ultrasonic sensors are deployed on the ceiling, by predefined form of the grid. The WSN nodes can perceive the real-time environment information under it, then occupancy grid map is constructed by data discretization, then the dynamic model is get. This Thesis introduces D*Lite algorithm and PRM algorithm to plan a shorted path for mobile robot in dynamic environments. Simulation results show that D*Lite algorithm can re-plan, and significantly reduce dynamic path planning time in the environment filled with obstacles.