emss - Environment Mapping Self-Sustainable Robot

The aim of the emss project is to tackle the problems of a self-sustainable, environment mapping robot in a bottom up approach. The major challenges imposed by such a mobile robot include the assembly of hardware, and more importantly the necessary software algorithms for localization, navigation, and discovery. Using ready-made hardware, much of the time-consuming electrical engineering problems have been avoided, allowing a strong focus on software. However, many hardware modifications have been undertaken to better suit the needs of the project. Building upon previous work achieved in our Semester Project, where a part of the necessary hardware and software was developed, the goal of this Bachelor Thesis is to create a basic environment map of obstacles and floor plan to the most accurate degree possible with the given hardware and datasources, all while safely navigating and exploring the area. In addition, third-party applications, such as a Wireless Positioning System, must be able to connect to the emss framework and make use of the positioning data for their own purposes. The emss framework, consisting of a set of “hot-swappable” modules written in C++, provides an extensible design, which allows a wide array of functionality and supports different strategies for the same problem. The framework features a full blown multithreaded software stack which allows the autonomous controlling and interfacing of the robot. The Hardware Abstraction Layer allows for the complete emulation of the underlying hardware, achieved largely by reverse engineering the behavior of the proprietary hardware. Safe navigation has been achieved by intelligently avoiding drops, obstacles, and walls. Furthermore, small areas can be autonomously navigated and mapped using different space-filling algorithms and map structures. Collaboration with third-party software has been realized with the Wireless Positioning System PointZero by automatically collecting necessary signal reference points. Other routine tasks, such as docking the robot on its docking station, have been implemented. In this paper we present an accurate description how these tasks have been realized, our assessment of the results, and insights into future improvements.