A Master of Science Thesis in Mechatronics submitted by Islam Mohammad -Amin Al-Jarrah entitled, "Indoor Localization Schemes for Mobile Robots," submitted in November 2010. Available are both soft and hard copies of the thesis.
Mobile robots have taken a major role in indoor environments where they are used to accomplish high risk tasks instead of human beings, for example in war circumstances, dangerous chemical interactions, etc. Localization of a mobile robot is the problem of determining the location of the robot as it navigates within an environment. Localization of mobile robots outdoors is mainly done based on GPS (Global Positioning System). GPS consists of several satellites orbiting the earth and broadcast data to indicate location and current time. The distance is determined by the time for the signals to reach the receiver from at least four satellites. The GPS system works well for outdoor terminals but cannot be used indoors because it needs a line-of sight between the satellites and the receiver. Other localization techniques based on sensors like sonar, infrared, cameras, etc. are used for indoor localization, but these sensors need intensive processing to get accurate readings, in addition to other limitations such as sonar's beams collision, cost, cameras resolution and image processing time delays. In this research, a different technique based on Wireless Sensor Networks (WSN) has been investigated for mobile robot localization. In particular, we investigate four scenarios for the target localization which are localization using static motes only, dynamic motes only, cooperative hybrid model and hybrid model. The proposed system utilizes a combination of static and mobile sensor nodes to collaborate in localizing and capturing a target using wireless transmission. Static nodes guide mobile nodes into localizing the target using some of the special characteristics of the target like signal strength, frequency, sound, temperature, etc. Each mobile node will gather information about the target and execute an algorithm to set its trajectory towards the target. Each mobile node will share its knowledge with others to improve their localization decision. The implemented system has several features. First, it achieves good accuracy because of the involvement of many nodes in the estimation process and the communication between mobile and static motes to localize the target. Second, it is robust to node failure since if one of the nodes is not working the rest of motes can collaborate to compensate for the missing data and localize the target accurately. Simulation results of localization based on static, dynamic, hybrid, and co-hybrid models are presented in this report. Comparison of the results of the various simulated models is based on Mean Square Error MSE of the localization and received Signal-to-Noise ratio (SNR). It is shown that localization using static motes outperformed other models. Using the same criteria, the Hybrid & Co Hybrid localization models were next in performance. Target localization based on dynamic motes gave the worst performance. The effect of wireless channel shadowing on the performance of the proposed schemes is also presented.