engineering

Steven M. LaValle

Steven M. LaValle is a engineering 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 Steven M. LaValle rather than just read about it. In short: Steven M. LaValle (born 1968 in St.

Key takeaways

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

Reference excerpt

Steven M. LaValle (born 1968 in St. Louis, Missouri) is an American computer scientist, and a professor in the Faculty of Information Technology and Electrical Engineering at the University of Oulu. He was also an early founder and head scientist of Oculus VR until it was acquired by Facebook in 2014. He is best known for his work on rapidly exploring random trees (RRTs), the Oculus Rift, and his book, Planning Algorithms, one of the most highly cited texts in the field.

Academic career LaValle received his BS, MS, and PhD degrees in Electrical and Computer Engineering at the University of Illinois Urbana–Champaign in 1990, 1993, and 1995, respectively. From 1995 to 1997, he was a post-doctoral researcher and lecturer in the Computer Science Department at Stanford University. From 1997 to 2001, he was an assistant professor in the Department of Computer Science at Iowa State University. From 2001 to 2018, he was on the faculty in the Department of Computer Science at the University of Illinois Urbana–Champaign, as a full professor. Since 2018, he has been a professor at the University of Oulu in Finland. He has published over 150 articles, in which most of his earlier works were in the area of robot motion planning. In addition to introducing RRTs, he coined the term "sampling-based motion planning" and developed numerous planning algorithms for handling typical control-theoretic problems such as kinematic constraints, momentum, feedback, multiobjective optimality, and stochastic uncertainty. His more recent research has focused on understanding the minimal information requirements for robot systems, leading to simpler sensor fusion methods and mathematical models that help to reduce complexity of robots (informally, their brain size) that are designed for particular tasks. He has published three textbooks, all of which are freely available online. In addition to "Planning Algorithms", mentioned above, he wrote books titled Sensing and Filtering and Virtual Reality.

Oculus VR During a leave of absence from the University of Illinois, LaValle started working from Oulu, Finland for Oculus VR in September 2012, a few days after their Kickstarter campaign. He served as their principal scientist from March 2013 until the company was acquired by Facebook in July 2014, addressing virtual reality challenges "including sensor fusion, magnetic drift correction, and kinematic modeling" while disseminating the company's technical achievements in a science blog. He developed head tracking methods for the core software, based on IMUs and computer vision, and led a team of perceptual psychologists to provide principled approaches to virtual reality system calibration and the design of comfortable user experiences. He was a coauthor of the first Oculus SDK Overview. He is a co-inventor on two Oculus VR patents. One (with Peter Giokaris) is for perception based predictive tracking for the Oculus Rift, which was crucial in reducing perceived tracking latency. The other is for sensor calibration and filtering methods, which were important for highly accurate, low-latency tracking.

Other industry Since 2014, LaValle has been an active angel investor and adviser to startup companies and venture capitalists, in the areas of virtual and augmented reality, and robotics. From 2016 to 2017, he was a vice president and the Chief Scientist of VR/AR/MR at Huawei Technologies Co. Ltd. He is also one of the International Collaborators for Experiential Technology Innovation Centre (XTIC), an IIT Madras Institute of Eminence Centre in Virtual Reality and related fields, at IIT-Madras, and awarded XTIC Award 2024 for Innovation to A.R. Rahman for his visionary work on the groundbreaking VR film, Le Musk, at IIT-Madras on 17 November 2024.

Awards and honors In 2012 LaValle was named "University Scholar" along with six other professors at the University of Illinois Urbana-Champaign. During 2015, he was featured on displays offering expert perspective in the Robot Revolution exhibit at Chicago's Museum of Science and Industry. In 2019, LaValle (with James J. Kuffner Jr.) received the Milestone Award from the International Conference on Robotics and Automation, for the most impactful paper (among around 3000) published between 1997 and 2001.

References

External links Home page of Steven M. LaValle

Illustrations

Worked examples

Example 1 — a first encounter with Steven M. LaValle

Start with the simplest possible case. Write down what Steven M. LaValle claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, 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 Steven M. LaValle 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 Steven M. LaValle 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 Steven M. LaValle

In research: Steven M. LaValle appears in engineering 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 Steven M. LaValle 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: Steven M. LaValle is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1968 births, American artificial intelligence researchers, American control theorists, so understanding it makes those chapters shorter.
In everyday life: Look for Steven M. LaValle 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.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Steven M. LaValle” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Steven M. LaValle in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Steven M. LaValle 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 Steven M. LaValle out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Steven M. LaValle in simple terms?

Steven M. LaValle (born 1968 in St.

Why does Steven M. LaValle matter?

Because it connects several engineering 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 Steven M. LaValle?

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 Steven M. LaValle.