Machine Learning Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Mendel HMM Toolbox for Matlab Written by Steinar Thorvaldsen, 2004. Last updated: Jan. 2006. Dept. of Mathematics and Statistics University of Tromsø - Norway. steinart@math.uit.no MendelHMM is a Hidden Markov Model (HMM) tutorial toolbox for Matlab. To run the program you should make the following steps: 1. When you type "mendelHMM" in Matlab command window the main window of GUI will appear. Main window of the program. In his historic experiment, Gregor Mendel (1822-1884) examined 7 simple traits in the common garden pea (Pisum). Today we know that the recessive expressions most often are mutations in the DNA molecule of the gene, as it is well known for Mendel’s growth gene (trait 7) where a single nucleotide G is substituted with an A. In his experiment Mendel also studied in more detail the plant seeds with two and three heredity factors simultaneously. The estimate of a statistical model according to a training set There are two main types of learning. The sampling of new training data y = (A, A, a, a, a) 1. 2. 3.
Robot Navigation Edited by Alejandra Barrera, ISBN 978-953-307-346-0, 250 pages, Publisher: InTech, Chapters published July 05, 2011 under CC BY-NC-SA 3.0 licenseDOI: 10.5772/705 Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments.
General Hidden Markov Model Library | Free Science & Engineering software downloads Introduction to Robotics - Fall 2011 | Correll Lab This class will teach the basics of how robots can move (locomotion and kinematics), how they can sense (perception), and how they can reason about their environment (planning). Lecture materials are supported by computer exercises using the simulation software “Webots” (right). Exercises will cover programming of basic sensors, actuators and perception algorithms and are geared to prepare the students to participate in the online competition “RatsLife” ( within the framework of the class. In RatsLife, two miniature robots “E-Puck” are competing against each other in a virtual maze for available chargers. The students will work in teams of 2 to 3 and develop controllers for the robots putting concepts taught in class into practice. Students will also have the ability to launch their controllers on a set of real e-Puck robots. Prerequisites: programming experience in C/C++ and/or Java. The “Introduction class” is offered as CSCI 3302 and ECEE 3303 in Fall 2011.
Online Code Repository The goal is to have working code for all the algorithms in the book in a variety of languages. So far, we have Java, Lisp and Python versions of most of the algorithms. There is also some old code in C++, C# and Prolog, but these are not being maintained. We also have a directory full of data files. Let peter@norvig.com know what languages you'd like to see, and if you're willing to help. Supported Implementations We offer the following three language choices, plus a selection of data that works with all the implementations: Java: aima-java project, by Ravi Mohan. Unsupported Implementations Implementation Choices What languages are instructors recommending? Of course, neither recall nor precision is perfect for these queries, nor is the estimated number of results guaranteed to be accurate, but they offer a rough estimate of popularity.
Advanced Robotics Spring 2013 | Correll Lab This class is the follow-up class to CSCI3302 “Introduction to Robotics”. Robots perceive their environment with signal processing and computer vision techniques, reason about them using machine learning, artificial intelligence and discrete algorithms, and execute their actions based on constraints imposed by sensor uncertainty, their mechanism, and their dynamics. “Advanced Robotics” will teach the key concepts used by manipulating robots and provide hands-on experience with state-of-the-art software and systems. Lecture materials are supported by exercises around the “Robot Operating System” ROS and will lead to the completion of a group project. Meetings: The class will meet MWF from 1-1.50pm in ECR 108 and in ECCS 1B21 for exercises. Due dates: This class has three two week homework assignments. This is a 4830/7000 “Special Topics” class. Prerequisites: CSCI3302 (only for CS4830 students) The overarching goal of this class is to implement an autonomous greenhouse. Final Projects 1.
Robotics, Vision & Control The practice of robotics and computer vision each involve the application of computational algorithms to data. The research community has developed a very large body of algorithms but for a newcomer to the field this can be quite daunting. For more than 10 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This new book makes the fundamental algorithms of robotics, vision and control accessible to all. "An authoritative book, reaching across fields, thoughtfully conceived, and brilliantly accomplished!"
Our First Experience with Robotics: Making a Web-Controlled Robotic Arm As part of Programmers’ Day celebration this year, Azoft web developers decided to surprise our fellow Azoft employees with a competition. To try something new and unusual, we created an internet-controlled robotic arm. This was our first experience with robotics and it turned out a success. The robotic arm competition was lots of fun for everyone involved, so we decided to share our experience and post this robotics tutorial to give you a fast start into building robots for your own geek parties. What does the robotic arm do? Our robotic arm is controlled via a web interface: it responds to remote commands and performs simple tasks. The tasks could vary: from drawing lots in a lottery to grabbing objects and collecting them in a basket - it’s up to your imagination. Have you decided what your robot will be doing? You will need microcontroller TI Stellaris Launchpad two servos (one for rotates, one for lifts) Hitec HS-322 servo TowerPro SG90 for the hand Let's get started 0. Stage 0. 1.
The Pilot Hello all. Welcome to my blog. This space will be all about what I have learnt and/or done at my hostel room, the various laboratories in college or at my home sweet home. The content shall be mostly stuff that the curriculum doesn't cover. I will try to present the content in an informal manner directly from my experience. Please note, I may not have practically done 'each and every thing' that I write about in this space, but I can say with a fair amount of confidence that even if I discuss something that I have not yet undertaken myself, utmost care shall be taken to ensure that the topic is researched to the best of my ability and shall be of help to the reader in his/her endeavors. Lastly, I do not claim that what I write is the absolute truth and the best content available. Also, please feel free to comment, ask questions, answer questions, offer constructive suggestions to make this blog a better effort.
Beginning Embedded Electronics - 1 This is a series of lectures written for those with mild electronics background (aka Sophomore in Electrical and Computer Engineering) to learn about the wild world of Embedded Electronics. I assume only that you know what electricity is and that you've touched an electrical component. Everything else is spelled out as much as possible. You can get all the parts for this lecture here. Sorry for the confusion. What's a Microcontroller? You may know what an OR gate is. A microcontroller is the same as an OR gate. if (A == 1 || B == 1) else It's C code! In the old days, microcontrollers were OTP or one-time-programmable meaning you could only program the micro once, test the code, and if your code didn't work, you threw it out and tried again. Flash micros are different than computers and RAM. Now back to that OR gate IC. if (PORTC.2 == 1) then do something… Each output pin can be pushed high or low. while(1) RB3 = 1; delay_ms(1000); RB3 = 0; delay_ms(1000); Guess what that code does? Ok!
Make a Scribbling Machine Collect these things: 1.5-3.0 volt motor [link]Note: You can find motors in all sorts of mechanical toys and common household objects; we encourage you to salvage one instead of buying it! AA battery A piece of hot melt glue stick Broccoli band (thick rubber bands used for produce) Markers Recyclable container such as a strawberry basket or yogurt cup Masking tape Paper for testing Some other helpful materials: Clothespins; Popsicle sticks; wood skewer sticks; pipe cleaners; wire; nuts, washers, or other small weights; wire stripper; scissors; small screwdriver; googly eyes.