The course content will be delivered within about 8-10 seminars/workshops.
Students with a degree such as doctoral students and master students holding a bachelor degree.
The course was last given
After finishing this course successfully students will know about basic principles of robotics systems. They will understand how robotic systems perceive their environment, localize, plan, act, and coordinate their actions. Within the course, students can focus on specific topics, which can be related to their own research.
Prerequisites are basic knowledge in linear algebra, data structures and algorithms, as well as programming in C++/Linux. Some background in artificial intelligence will be useful.
This course presents an overview on methods and algorithms in robotics. In more
particular we will discuss popular topics in this context, such as sensing and
state estimation, simultaneous localization and mapping (SLAM), search
algorithms and motion planning, and coordination by heterogeneous multi robot
The goal of this course is to teach students preliminary algorithms and methods that are building the foundations for truly autonomous robot systems that have been deployed in real-world scenarios up to this date. The course is very much related to the practical application of robotics. In fact, examples from the fields of Security and Rescue Robotics will accompany the material taught during each seminar.
Preliminary list of topics covered:
- Introduction to Robotics
- Fundamental Robot Architectures
- Robot Motion Planning
- Sensing & State Estimation
- Localization & Mapping (SLAM)
- Cooperative Sensor Perception
- Robot Exploration and Search
- Robot Coordination
The course will be structured into two parts. During the first part, students will be given seminars introducing basic concepts of robotics. During the second part, students will focus on a specific topic and prepare a paper and/or implementation on this topic. They will finally present and discuss their topic at the end of the course.
S. Thrun, W. Burgard, and D Fox. Probabilistic robotics. 2005. Cambridge, MA:
Steven M. LaValle, Planning Algorithms. 2006. Cambridge University Press. Available for download at: http://planning.cs.uiuc.edu/
Active participation in seminars and final paper, discussion, and presentation.
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