astronomy

Wolfram Burgard

Wolfram Burgard is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Wolfram Burgard rather than just read about it. In short: Wolfram Burgard (born 1961 in Gelsenkirchen, Germany) is a German roboticist. He is a full professor at the University of Technology Nuremberg where he heads the Laboratory for Robotics and Artificial Intelligence.

Key takeaways

Wolfram Burgard belongs to astronomy; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Wolfram Burgard to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Wolfram Burgard from memory before moving on to harder problems.

Reference excerpt

Wolfram Burgard (born 1961 in Gelsenkirchen, Germany) is a German roboticist. He is a full professor at the University of Technology Nuremberg where he heads the Laboratory for Robotics and Artificial Intelligence. He is known for his substantial contributions to the simultaneous localization and mapping (SLAM) problem as well as diverse other contributions to robotics.

Biography

Education Wolfram Burgard received his Diploma degree from University of Dortmund in 1987 and his Doctorate from the University of Bonn in 1991. His thesis advisor was Armin B. Cremers.

Career In 1991 he became a research assistant at the University of Bonn, where he led the laboratory for Autonomous Mobile Systems. He was head of the research group that installed the mobile robot Rhino as the first interactive museum tour-guide robot in the Deutsches Museum Bonn, Germany in 1997. In 1998, he and his colleagues deployed the mobile robot Minerva in the National Museum of American History in Washington DC. In 1999, Wolfram Burgard became Professor for Autonomous Intelligent Systems at the Albert-Ludwigs-Universität Freiburg. In 2022, he became Professor for Robotics and Artificial Intelligence as well as Founding Chair of the Department Engineering of the University of Technology Nuremberg.

Research Together with his colleagues, Wolfram Burgard developed numerous probabilistic approaches to mobile robot navigation. This includes Markov localization, a probabilistic approach to mobile localization that can robustly track the position of a mobile robot, estimate its global position when it starts without any prior knowledge about it, and even recover from localization failures. In 1999, Frank Dellaert, Dieter Fox, Sebastian Thrun, and Wolfram Burgard developed Monte Carlo localization, a probabilistic approach to mobile robot localization that is based on particle filters. Wolfram Burgard and his group have also made substantial contributions to the simultaneous localization and mapping (SLAM) problem, which is to determine the map of the environment and the position of the robot at the same time. Wolfram Burgard together with his long-term collaborators Dieter Fox and Sebastian Thrun is a co-author of the book Probabilistic Robotics. He also is a co-author of the book Principles of Robot Motion - Theory, Algorithms, and Implementations, together with Howie Choset, Kevin M. Lynch, Seth A. Hutchinson, George Kantor, Lydia E. Kavraki and Sebastian Thrun. Wolfram Burgard has the 2009 Gottfried Wilhelm Leibniz Prize, the most prestigious German research prize. He has furthermore received seven best paper awards from outstanding conferences. He also became a distinguished lecturer of the IEEE Robotics and Automation Society. In 2008, Wolfram Burgard became a fellow of the European Coordinating Committee for Artificial Intelligence. In 2009, Wolfram Burgard became a fellow of the Association for the Advancement of Artificial Intelligence. In 2010, he received an Advanced Grant from the European Research Council.

Students Wolfram Burgard supervised several PhD students in his lab for Autonomous Intelligent Systems, namely Maren Bennewitz (2004), Dirk Haehnel (2005), Cyrill Stachniss (2006), Rudolph Triebel (2007), Óscar Martínez Mozos (2008), Patrick Pfaff (2008), and Christian Plagemann (2008), Jürgen Sturm (2011), Daniel Meyer-Delius Di Vasto (2011), Slawomir Grzonka (2011), Thilo Grundmann (2012), Kai Wurm (2012), Axel Rottmann (2012), Barbara Frank (2013), Rainer Kümmerle (2013), Bastian Steder (2013), Jörg Müller (2013), Dominik Joho (2013), Boris Lau (2013), Maximilian Beinhofer (2014). A large fraction of his publications are available at Google Scholar.

References

External links Wolfram Burgard's home page Wolfram Burgard's former home page Wolfram Burgard's former research group

Illustrations

Worked examples

Example 1 — a first encounter with Wolfram Burgard

Start with the simplest possible case. Write down what Wolfram Burgard claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Wolfram Burgard before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Wolfram Burgard ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Wolfram Burgard

In research: Wolfram Burgard appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Wolfram Burgard in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Wolfram Burgard is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1961 births, Fellows of the Association for the Advancement of Artificial Intelligence, Fellows of the European Association for Artificial Intelligence, so understanding it makes those chapters shorter.
In everyday life: Look for Wolfram Burgard outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Wolfram Burgard in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Wolfram Burgard means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Wolfram Burgard out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Wolfram Burgard in simple terms?

Why does Wolfram Burgard matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Wolfram Burgard?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Wolfram Burgard.