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Margarita Chli

Margarita Chli is a computer science 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 Margarita Chli rather than just read about it. In short: Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping.

Margarita Chli — main illustration
Margarita Chli — illustration

Key takeaways

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

Reference excerpt

Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping. Chli is also the Vice Director of the Institute of Robotics and Intelligent Systems and an Honorary Fellow of the University of Edinburgh in the United Kingdom. Her research currently focuses on developing visual perception and intelligence in flying autonomous robotic systems.

Early life and education Chli grew up in Cyprus and Greece. She pursued her undergraduate degree at the University of Cambridge in the United Kingdom. She conducted her studies in Information and Computer Engineering at Trinity College. After receiving her bachelor's degree, she continued at Trinity to conduct her Masters in engineering as well. In 2006, Chli pursued her graduate work at Imperial College London under the mentorship of Andrew Davison. She worked in the Robot Vision Group where she worked towards developing novel ways to manipulate data to enable efficient autonomous navigation of mobile devices. Since vision-based methods are the key to enabling autonomous navigation, Chli tried to address the challenges that lie in preserving precision while achieving efficient information processing. She used the principles of Information Theory to guide the estimation based decisions made after gathering information from the environment and showed that these principals improved the efficiency and consistency of the algorithms used to estimate motion and form probabilistic maps of the environment. Her algorithms also enabled dense feature mapping even in the presence of ambiguity and inconsistencies in camera dynamics. Chli completed her graduate work in 2009 and worked for one year as a research associated in the Robot Vision Group.

Career and research After completing her PhD, Chli joined the Autonomous Systems Lab at ETH Zürich for her postdoctoral research, and soon became the Lab Deputy Director. While at ETH Zürich, she taught the Autonomous Mobile Robot Course, and this was later turned into an online course to train thousands of researchers worldwide for free. In 2013, Chli was awarded the Chancellor's Fellowship, and became an assistant professor at the Institute of Perception Action and Behavior at the University of Edinburgh. She held this prestigious fellowship for two years. In 2015, Chli was promoted to the Swiss National Science Foundation (SNF) Assistant Professor in Vision for Robotics at ETH Zürich and relocated her lab from Edinburgh. She still holds an Honorary Fellowship at the University of Edinburgh. Her lab, the Vision for Robots Lab, or V4RL, focuses on developing intelligence robots to improve the quality and safety of human life. Chli has several lines of research going on in her lab to achieve these goals. With the SHERPA project, Chli aims to use intelligent and autonomous robotic systems to help with alpine search and rescue. Chli also participates in research towards the myCopter project whose goal is to design personal automated aerial transportation systems such that one could travel from work to home by air at low altitudes. Lastly, Chli's team develops methods to enable micro aerial vehicles to map out unknown environments through the SFly project (Swarm of micro flying robots). All of these projects require immense innovations in the field of computer vision and robotics, essentially demanding the ability that robots can handle large amounts of data in efficient ways to “see” their environments and respond quickly and autonomously. Chli's team aims to develop these intelligent systems with the capability of visual perception through the use of deep learning and robot collaboration.

Improving methods of computer vision Chli's early work helped to improve computer vision approaches to enable the construction of autonomous robotic systems. Chli first tackled the issue of simultaneous localization and mapping (SLAM) in which a robotic system has difficulty estimating its new and changing environment while also keeping track of its own location. Since dividing the map into smaller submaps would allow for individual parts of a scene to be processed independently and thus more efficiently, Chli created an innovative method to perform submap division on SLAM maps. She used hierarchical clustering to group similar features together into subgroups and she revealed novel insight into the structure of visual maps which helped to guide the field in addressed the computational issues associated with SLAM. The next computer vision issue that Chli tackled during her time as a postdoctoral fellow at ETH Zürich, was key point detection in images. She developed a method called BRISK (Binary Robust Invariant Scalable Key points) and it performed much faster and at a much lower computational cost compared to previous key point detection algorithms such as SURF and SIFT.

Autonomous helicopter During Chli's postdoctoral work at ETH Zürich, she was part of a team that developed the first autonomously flying small helicopter. The helicopter had a monocular camera as the only inertial sensory and was able to navigate in novel environments. It achieved SLAM with extreme robustness to enable its autonomous flight.

… excerpt ends here. Continue reading the full article.

Illustrations

Margarita Chli illustration

Worked examples

Example 1 — a first encounter with Margarita Chli

Start with the simplest possible case. Write down what Margarita Chli claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, 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 Margarita Chli 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 Margarita Chli 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 Margarita Chli

In research
Margarita Chli appears in computer science 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 Margarita Chli 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
Margarita Chli is common in secondary-school and first-year university syllabi. It links to neighbouring topics Academic staff of ETH Zurich, Alumni of Trinity College, Cambridge, Alumni of the Department of Computing, Imperial College London, so understanding it makes those chapters shorter.
In everyday life
Look for Margarita Chli 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 Margarita Chli in 20 minutes

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

Frequently asked questions

What is Margarita Chli in simple terms?

Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping.

Why does Margarita Chli matter?

Because it connects several computer science 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 Margarita Chli?

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 Margarita Chli.

Tags

  • Academic staff of ETH Zurich
  • Alumni of Trinity College, Cambridge
  • Alumni of the Department of Computing, Imperial College London
  • Greek computer scientists
  • Living people
  • Roboticists
  • Women roboticists

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