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Summer Camp - Introductory Summer Camp - Advanced Summer Camp - Underwater Robotics & Communication Faculty


Summer School - Advanced Intelligent Systems

Synopsis

  • Exposure to research topics at cutting edge of Intelligent Systems.
  • Global faculty.
  • Concept based practical and theoretical learning.
  • Opportunity to conduct original research and publish a conference paper.
  • Cost of entire training program including taxes.
  • Study material and software on CD.
  • Certificate.

In keeping with the pioneering spirit at IURS, we have worked very hard over the last few months in order to design an Advanced Intelligent Systems summer school that would not only expose participants to higher level concepts in Robotics, but other areas of smart computing as well and prepare them to step in to a world of true thinking-adapting machines.

From concepts such as advanced computer vision that make locating patterns and objects easy, to building maps from Laser scans or deriving robot odometry from infra-red scans this course will cover it all. Not only this, but concepts from sensor networks and machine learning will be covered as well! Since every concept covered in the workshop requires a good grasp in order to proceed forward, practical exercises will be interwoven in to each step in order to provide the best learning opporunities.

For this course as well IURS has engaged not only its own team members, educated in India and abroad, as faculty but also talented researchers who hail from or studied in USA, Canada, Germany, Romania and Hungary, not as guest lecturers but as faculty for the course.

At the end of the course participants will be able to choose a faculty member to work on a project over the course of a month and then publish the obtained results in a suitable conference or journal to enhance their own academic experience. The course will not only teach students concepts but will dip their hands deep in to intelligent systems reasearch by giving them an opportunity to conduct original scholarly work.

Prerequisites: Familiarity with programming in C/C++ and MATLAB for analysis work.

Registration Deadline : 30 Jun 2009 (On spot may also be accepted for higher charges)

Dates:

1 Jul 2009 - 10 Jul 2009

Timings: 4.00PM to 6.00PM.

Duration: 20 hrs initial program + project work in contact and guidance of researcher.

Venue

Indian Retail School
New Delhi

Accommodation: Assitance in securing a place will be provided - please ensure you inform us that you will need accommodation.

Course Contents

  • Sensor Networks
    • Hardware architecture.
    • Topologies.
    • Synchronization mechanisms.
    • Scheduling algorithms.
       
  • Advanced Sensing & Computer Vision
    • Pattern matching .
    • Object location.
    • Scene matching.
    • Scan matching.
    • 2D & 3D map construction.
    • Feature extraction.
    • 3D Point Cloud Processing.
    • Scale Invariant Feature Transforms.
    • Plane matching & fitting.
    • Region growing.
    • Pose estimation
    • Visual SLAM.
    • Expedited registration mechanisms.
    • Iterative closest point matching (ICP).
    • Human body recognition.
    • Odometry derivation.
       
  • Machine Learning
    • Artificial neural networks.
    • Recurrent neural networks.
    • Deep belief networks.
    • Simulated annealing.
  • Graphical & Visualization Methods
    • Graphics algorithms.
    • Computer visualization.
    • Information visualization.
    • Scientific visualization.
    • Uncertainty visualization.
 

Hands on Guided Tasks

Project
Description
Sensor Networks

Students will be introduced to common problems faced and tasks performed by researchers and engineers in the sensor networks field.

  • Introduction to TinyOS .
  • Using radio connected timer operated blink controls.
  • Remote data collection & logging.
  • Using the ActiveMessage components.
  • Biologically inspired synchronization .

The goal of the exercise will be to familiarize students with the structure of TinyOS, a commonly used OS in the sensor networks field, and have them write applications that deal with common problems .

Plane Fitting

This combination of exercises will try to motivate the need of 3d sensors like
stereo cameras and the need of plane fitting on the data provided by this sensors. It will introduce two intersting algorithms for plane fitting that are suitable for robotics, namely region growing plane fitting algorithm and plane fitting based on mixture of gaussians.

During the course, students will get to implement plane fitting based on mixture of gaussian and use it for tracking the translation of the robot.

Machine Learning

This set of exercises will start with a broad introduction to machine learning techniques. It will go through mixture of gaussian models, parzen windows, simulated anealing, fuzzy logics, baysian networks, and end with neuronal networks.

A new intersting type of recurrent neural networks will be presented, namely echo state networks. After each chapter the techniques learned will be used in short practical experiments that will include pattern recognition or decision taking.

Visual SLAM

Increase in the usage of 3D sensing systems means that sensors like IR Swiss Rangers, stereo cameras and other ToF systems provide not only intensity images but 3D point clouds that are noisy in nature, however, extremely useful if this noisy data can be accurately processed.

This exercise in the course will deal with processing such 3D point clouds in order to find persistent features in them that are invariant to scale and rotation and also to some degree of illumination changes. Furthermore, these features will then be matched between 3D point cloud sets to perform scene matching, object detection, pattern detection, map building and a quick form of known-correspondence registration introduced in order to derive robot odometry for performing Visual SLAM with the aid of these recognized features.

Grand Symphony

The last project of the course has been termed the grand symphony, because having learnt concepts of Machine Learning and Advanced Sensory data processing and also having performed practical exercises all through related to each concept, the students will work towards the common goal of building a project that combines knowledge learnt from all the topics in the class.

At the moment the final guided research project topics are shortlisted as:

  • 3D Map building using visual markers.
  • Real-time robot odometry derivation from 3D point clouds.
  • Uncertainty calculation and visualization in 3D maps.
The students will be free to propose topics and ideas for a final project themselves as well. The students will work under supervision and mentorship of the faculty to complete the projects in a few weeks after the course.

Results of the projects will be translated in to research papers that will be submitted to conferences/journals as per their research merit.

Cost:

Registration Payment Received By
Amount
Jun 25, 2009

Rs. 6,500

Course Description

Having had an introduction to basic concepts of robotics and intelligent systems, this course is designed to blow the doors guarding the steps of intelligent systems research wide open.

Students will not only be introduced to cutting edge research topics, but will also have an opportunity to work upon these brand new ideas and concepts that are barely being introduced in to the research community itself as well. Working with sensor data from Stereo Cameras, Swiss IR Rangers and Laser Range Finders, while applying advanced Machine Learning concepts the students will have an opportunity to experience the cutting-edge techniques behind pattern matching, scene matching, visual SLAM and map building. Not only this but students will also be exposed to other intelligent systems concepts like sensor networks, which will prepare them to deal with not only robotics as an application field, but any field of intelligent systems.

A lot of the course work is based upon concepts that are brand new in research as well; for example, the SIFT is as recent as 2004. Working on these cutting edge technologies, the students of this course will truly be prepared to handle the upcoming developments in intelligent systems and contribute to those as well. After all, intelligent systems is not only restricted to robotics.

The Faculty

The faculty of this course has been educated, and even are from, the USA, Canada, India, Germany, Romania, Bulgaria and other countries. Having won many international meritorious awards and conducted research in the fields of intelligent systems and robotics, this diverse group of individuals is highly qualified to train students in this field. Moreover, experience in conducting various workshops in USA and India has given the faculty world-class experience in ensuring the highest levels of academic excellence throughout the course. Furthermore, students stand to benefit from this dynamic and highly talented faculty through the active research programs of IURS and their own home institutions, in which they are involved, as well. This faculty has won numerous international awards, published many papers and holds various patents in their relevant fields.

Click here for more information on the faculty.

 


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