Mobile Robotics (ETF AEO MR 5960) |
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General information |
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Module title | Mobile Robotics |
Module code | ETF AEO MR 5960 |
Study | ETF-B |
Department | Control and Electronics |
Year | 2 |
Semester | 3 |
Module type | Mandatory |
ECTS | 6 |
Hours | 60 |
Lectures | 45 |
Exercises | 15 |
Tutorials | 0 |
Module goal - Knowledge and skill to be achieved by students |
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| <br> Adoption of basic knowledge on motion, navigation and control of mobile robots. |
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Syllabus |
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| 1. Introduction. Basic concepts and definitions. Mobile robots classification. Motives for mobile robots development. Historical development of mobile robots. Mobile robots applications. Trends in mobile robotics development. <br> 2. Locomotion of mobile robots. Drive configurations of mobile robots: holonomic (differential drive, synchronous drive, 3-wheel drive, car drive) and nonholonomic (all-directional drives). Direct and reverse kinematics of drive configurations. Dynamics of mobile robots with differential drive. Walking robots. Kinematics of walking robots. <br> 3. Nonvisual sensors for mobile robots. Odometric sensors, orientation and perception sensors. Mobile robot's position computing using incremental encoder, absolute encoder and accelerometer. Orientation determination using gyroscope, compass and gyrocompass. Operation principles and characteristics of ultrasound sensors and laser rangefinders. <br> 4. Visual sensors - robot vision. CCD cameras. Visibility problems. Visibility applications in robotics. Camera geometry. Modelling image acquisition. Image characteristics: colour, optical flow, correlation, edges recognition, characteristics extraction. Computing distance from objects using camera. Use of multiple cameras. <br> 5. Mobile robots localization. Relative position measurement. Odometry and inertial navigation. Global position measurement. Landmark-based localization. Genuine and artificial landmarks. Triangulation. Uncertainty triangulation. Geometric dilatation of accuracy. Application of Kalman filtering in estimation and correction of position measurement error. Global positioning systems. <br> 6. Generating mobile robot's map. Metric and topological maps of space. Generating maps using sensors' readings. Presentation using spatial occupation. Sensor measured data fusion. Map refreshing. Probabilistic techniques applications in fusion and in generating a map. Bayesian and Dempster-Shafer techniques. <br> 7. Path planning. Defining a path planning problem. Configurational space. Roadmap planning algorithm. Visibility graph. Voronoi diagrams. Cell-decomposition-based path planning. Potential fields method. Circumvention of obstacles. Bug (hybrid) algorithm of path planning. Vector fields histograms. <br> 8. Mobile robots control. Control structures: model, reactive, behavioural and hybrid structures. Planned control systems. Perception-design-action and perception-model-design-action. Generating behaviour and layers of behaviour. Basic schemes of behavioural control: motor-scheme and subsumtion. Competence levels and control levels. Example of speed controller and mobile robot's position synthesis using intelligent control algorithms. <br> |
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Literature |
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| Recommended | 1. Lecture notes and slides (will be available at the Web site). <br> 2. Dudek, G. & Jenkin, M. (2000). Computational Principles of Mobile Robotics, Cambridge University Press, Cambridge, UK. <br> 3. Siegwart, R. & Nourbakhsh, I. (2004). Introduction to Autonomous Mobile Robots, MIT Press, Cambridge, Massachusetts, USA. <br> |
| Additional | 1. Arkin, R.C. (1998). Behaviour-Based Robotics, MIT Press, Cambridge Massachusetts, USA. <br> 2. Nehmzow, U. (2006). Mobile Robotics: A Practical Introduction, Springer Verlag, Heidelberg, Germany. <br> 3. Gee, S.S. & Lewis, F. (2006). Autonomous MobileRobots: Sensing, Control, Decision Making and Applications, CRC Press, Boca Raton, USA. <br |
Didactic methods |
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| Lectures, laboratory, seminars. | |
Exams |
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| Participation in classes (10%), laboratory works (20%), seminar (50%), final exam (20%). <br> |
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Aditional notes |
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