Today at 15:30 - Davide Scaramuzza - Vision-Based Navigation: a Ground and a Flying Robot Perspective
by Announcements of talks＠IDSIA
Talk today at 15:30 at IDSIA
Galleria 1 Meeting room
Speaker: Davide Scaramuzza
Lab webpage: http://rpg.ifi.uzh.ch
Homepage: https://sites.google.com/site/scarabotix/
Affiliation: University of Zurich, Artificial Intelligence Lab
Title: Vision-Based Navigation: a Ground and a Flying Robot Perspective
Abstract
Over the past two decades, we have assisted to a rapid research
progress in driver assistance systems. Some of these systems have even
reached the market and have become nowadays an essential tool for
driving. GPS navigation systems are probably the most popular ones.
They have revolutionized the way of traveling and certainly
facilitated research towards fully autonomous navigation in outdoor
environments. However, there are still numerous challenges that have
to be solved in view of fully autonomous navigation of cars in
cluttered environments. This is especially true in urban environments,
where the requirements for an autonomous system are very high.
Another research area that lately received a lot of
interest—especially after the earthquake in Fukushima, Japan—is that
of micro aerial vehicles. Flying robots have numerous advantages over
ground vehicles: they can get access to environments where humans
cannot get access to and, furthermore, they have much more agility
than any other ground vehicle. Unfortunately, their dynamics makes
them extremely difficult to control and this is particularly true in
GPS-denied environments.
In this talk, I will present challenges and results for both ground
vehicles and flying robots, from localization in GPS-denied
environments to motion estimation. I will show several experiments and
real-world applications where these systems perform successfully and
those where their applications is still limited by the current
technology.
Finally, I will present our current research projects.
Short Biography
Davide Scaramuzza is Professor of Robotics at the Artificial
Intelligence Lab of the University of Zurich - where he leads the
Robotics and Perception Group - and Adjunct Faculty at ETH Zurich of
the Master in Robotics Systems and Control. He received his PhD (2008)
in Robotics and Computer Vision at ETH Z¨urich. He was Postdoc a both
ETH Zurich and the University of Pennsylvania, where he worked on
autonomous navigation of micro aerial vehicles. From 2009 to 2012, he
led the European project sFly, which focused on autonomous navigation
of micro helicopters in GPS-denied environments using vision as the
main sensor modality. For his research, he was awarded the Robotdalen
Scientific Awards (2009) and the European Young Researcher Award
(2012), sponsored by the IEEE and the European Commission. He is
coauthor of the 2nd edition of the book “Introduction to Autonomous
Mobile Robots” (MIT Press). He is also author of the first open-source
Omnidirectional Camera Calibration Toolbox for MATLAB (a popular
software simulation tool), which, besides thousands of downloads
worldwide, is also currently used at NASA, Philips, Bosch, and
Daimler. His research interests are field and service robotics,
intelligent vehicles, and computer vision. Specifically, he
investigates the use of cameras as the main sensors for robot
navigation, mapping, exploration, reasoning, and interpretation. His
interests encompass both ground and flying vehicles.
11 years, 10 months
Reminder: Multi-step time series forecasting
by Announcements of talks＠IDSIA
The talk will start at 11.00 sharp, so that interested person might then
attend also Monaldo's talk at 11.45.
Please take a jacket, since the room seems to be cold
:-)
WHEN
Tuesday (Feb 19, tomorrow) h. 11.00, room 223 (close to the vending machine)
TITLE : Bias and variance investigation for multi-step time series
forecasting
ABSTRACT :
Multi-step time series forecasting plays an important role in several
fields of science and engineering, such as economics, finance,
meteorology and telecommunication.
As in any estimation problem, the bias and variance decomposition of the
forecasting error is a fundamental concept whose understanding sheds
some light on the factors affecting the performance.
In the context of multi-step forecasting, others factors such as the
forecasting strategy and the forecasting horizon can have an impact on
the bias and variance components.
Using non-linear and linear simulated time series, we compare four
different forecasting strategies by decomposing their respective squared
error in noise, bias and variance components throughout the forecasting
horizon.
Experiments on real-world time series from two forecasting competitions
are also presented.
SPEAKER :
Souhaib Ben Taieb is a PhD candidate from Université Libre de Bruxelles
co-supervised by Gianluca Bontempi and Rob J. Hyndman. The topic of his
PhD thesis deals with machine learning strategies for multi-step
forecasting. He recently ranked among the top five competitors in the
Kaggle load forecasting competition.
11 years, 10 months
Multi-step time series forecasting
by Announcements of talks＠IDSIA
WHEN
Tuesday (Feb 19, tomorrow) h. 11.00, room 223 (close to the vending machine)
TITLE : Bias and variance investigation for multi-step time series
forecasting
ABSTRACT :
Multi-step time series forecasting plays an important role in several
fields of science and engineering, such as economics, finance,
meteorology and telecommunication.
As in any estimation problem, the bias and variance decomposition of the
forecasting error is a fundamental concept whose understanding sheds
some light on the factors affecting the performance.
In the context of multi-step forecasting, others factors such as the
forecasting strategy and the forecasting horizon can have an impact on
the bias and variance components.
Using non-linear and linear simulated time series, we compare four
different forecasting strategies by decomposing their respective squared
error in noise, bias and variance components throughout the forecasting
horizon.
Experiments on real-world time series from two forecasting competitions
are also presented.
SPEAKER :
Souhaib Ben Taieb is a PhD candidate from Université Libre de Bruxelles
co-supervised by Gianluca Bontempi and Rob J. Hyndman. The topic of his
PhD thesis deals with machine learning strategies for multi-step
forecasting. He recently ranked among the top five competitors in the
Kaggle load forecasting competition.
11 years, 10 months
[IDSIA] Talk Julian Togelius
by Announcements of talks＠IDSIA
Dear all,
I'm pleased to announce a talk by Julian Togelius, ex postdoc at IDSIA,
now associate professor at the Center for Computer Games
Research<http://game.itu.dk/>
,
IT University of Copenhagen <http://www.itu.dk/>.
The talk is on Tuesday, at 14:30, in the large room across the vending
machine room from IDSIA.
Cheers,
Giuse
************
WHEN: Tuesday, February 19; 14:30-15:00
WHERE: Room DSAN 222, the large one outside South IDSIA going
towards the RoboLab.
TITLE: Research in CI and AI for games at the IT University
of Copenhagen
ABSTRACT:
I will give a brief overview about current research on computational and
artificial intelligence in games in my group at the IT University of
Copenhagen. There is a wide assortment of interesting CI/AI challenges
motivated by modern computer games. Our projects include predicting player
behaviour and player emotions, automatically constructing levels,
environments, items and whole games, generating human-like playing styles,
and learning to play various games well. I will also ask what it would mean
for the game to play the player, and whether an AI needs to have fun.
11 years, 10 months