Perception. Read: AIMA Chapter 24 & Chapter HW#8 due today. Vision
|
|
- Barbra Thomasina Andrews
- 6 years ago
- Views:
Transcription
1
2 Perception Vision Read: AIMA Chapter 24 & Chapter 25.3 HW#8 due today
3 visual aural haptic & tactile vestibular (balance: equilibrium, acceleration, and orientation wrt gravity) olfactory taste magnetoreception others?
4 Body with 25 degrees of freedom (DOF) whose key elements are electric motors and actuators Sensor network, including 2 cameras, 4 microphones, sonar rangefinder, 2 IR emitters and receivers, 1 inertial board, 9 tactile sensors, and 8 pressure sensors Various communication devices, including voice synthesizer, LED lights, and 2 high-fidelity speakers Intel ATOM 1,6ghz CPU (located in the head) that runs a Linux kernel and supports Aldebaran s proprietary middleware (NAOqi) Second CPU (located in the torso) 27,6-watt-hour battery that provides NAO with 1.5 or more hours of autonomy, depending on usage
5 NAO has two cameras and can track, learn, and recognize images and faces. NAO sees using two 920p cameras, which can capture up to 30 images per second. The first camera, located on NAO s forehead, scans the horizon, while the second located at mouth level scans the immediate surroundings. The software lets you recover photos and video streams of what NAO sees. But eyes are only useful if you can interpret what you see. That s why NAO contains a set of algorithms for detecting and recognizing faces and shapes. NAO can recognize who is talking to it or find a ball or, eventually, more complex objects.
6 NAO is equipped with two sonar channels: two transmitters and two receivers. They allow NAO to estimate the distances to obstacles in its environment. The detection range is 0 70 cm. Less than 15 cm, there is no distance information; NAO only knows that an object is present.
7 Omnidirectional walking NAO's walking uses a simple dynamic model (linear inverse pendulum) and quadratic programming. It is stabilized using feedback from joint sensors. This makes walking robust and resistant to small disturbances, and torso oscillations in the frontal and lateral planes are absorbed. NAO can walk on a variety of floor surfaces, such as carpeted, tiled, and wooden floors. NAO can transition between these surfaces while walking. Whole body motion NAO's motion module is based on generalized inverse kinematics, which handles Cartesian coordinates, joint control, balance, redundancy, and task priority. This means that when asking NAO to extend its arm, it bends over because its arms and leg joints are taken into account. NAO will stop its movement to maintain balance.
8 Fall Manager The Fall Manager protects NAO when it falls. Its main function is to detect when NAO's center of mass (CoM) shifts outside the support polygon. The support polygon is determined by the position of the foot or feet in contact with the ground. When a fall is detected, all motion tasks are killed and, depending on the direction, NAO's arms assume protective positioning, the CoM is lowered, and robot stiffness is reduced to zero.
9 Audio NAO uses four microphones to track sounds, and its voice recognition and text-to-speech capabilities allow it to communicate in 8 languages.
10 Sound Source Localization One of the main purposes of humanoid robots is to interact with people. Sound localization allows a robot to identify the direction of sounds. To produce robust and useful outputs while meeting CPU and memory requirements, NAO sound source localization is based on an approach known as Time Difference of Arrival. When a nearby source emits a sound, each of NAO s four microphones receives the sound wave at slightly different times.
11 Sound Source Localization, continued For example, if someone talks to NAO on its left side, the corresponding sound wave first hits the left microphones, then the front and rear microphones a few milliseconds later, and finally the right microphone. These differences, known as interaural time difference (ITD), can then be mathematically processed to determine the current location of the emitting source. By solving the equation every time it hears a sound, NAO can determine the direction of the emitting source (azimuthal and elevation angles) from ITDs between the four microphones.
12 Signal Processing In robotics, embedded processors have limited computational power, making it useful to perform some calculations remotely on a desktop computer or server. This is especially true for audio signal processing; for example, speech recognition often takes place more efficiently, faster, and more accurately on a remote processor. Most modern smartphones process voice recognition remotely. Users may write their own signal processing algorithms directly in the robot.
13
14 to know what is where, by looking. (Marr) What are the characteristics of visual perception in people? What are the key open issues in computer vision?
15 Vision is a Constructive Process Your conscious perception of the visible world is an illusion manufactured by your brain (at great cost). Examples: brightness, color, and size constancy Vision Solves Specific Tasks in Specific Contexts Generality in visual skills tied directly to needs and context.
16 Vision is inferential: Light
17 Checker Shadow
18 Pixel color strongly affected by illumination. Perception of color constancy maintained by the brain (Images courtesy of David Heeger) Sunlight Fluorescent light
19 Object size vs. object depth (Images copyright John H. Kranz, 1999)
20 In each of the previous examples, the brain s goal is to maintain invariance to environmental effects: The amount and color of light in the scene The distance between the observer and an object of interest. How to achieve this invariance computationally? All other sensory experiences, such as audition and touch, are also the result of a constructive process.
21 question: Which aspects of the rich visual stimulus should be considered to help the agent make good action choices, and which aspects should be ignored? approaches 1. feature extraction computations applied directly to the sensor observations 2. recognition each agent distinguishes among the objects it encounters based on visual and other information 3. reconstruction agent builds a geometric model of the world from an image or set of images
22 edge detection texture analysis computation of optical flow (video sequence)
23 process of breaking an image into regions of similar pixels (a) Original image (b) Boundary contours (c) & (d) Segmentation into regions
24 Geometry-based Objects and images modeled as set of point/surface/volume elements Example real-time method: store geometric relationships in hash table Appearance-based Objects and images modeled as set of features closer to raw image Example real-time method: use histograms of simple features (e.g. color)
25 sources of appearance variation
26 (a) object models: images of a shoe and a telephone (b) a test image (c) the shoe and telephone have been detected by: finding points in the image whose features match a model
27 Object recognition in its full generality is a very hard problem. There are brightness-based and feature-based approaches Other possibilities? poking (i.e. experimenting) cf. Paul Fitzpatrick, formerly of MIT CSAIL, currently at Robot Rebuilt
28 Robot: We have got to find out where this object s boundary is. Camera: How are we going to do that? There's no way. Robot: Well there is one way. Looks reachable I say, let s poke it. (brandishes the Giant Poking Limb)
29 object segmentation poking affordance exploitation (rolling) edge catalog object detection (recognition, localization, contact-free segmentation) manipulator detection (robot, human)
30 Learning from an activity Poking: to learn to recognize objects, manipulators, etc. Chatting: to learn the names of objects Learning a new activity Searching for an object Then back to learning from the activity
Perception and Perspective in Robotics
Perception and Perspective in Robotics Paul Fitzpatrick MIT CSAIL USA experimentation helps perception Rachel: We have got to find out if [ugly naked guy]'s alive. Monica: How are we going to do that?
More informationROMEO Humanoid for Action and Communication. Rodolphe GELIN Aldebaran Robotics
ROMEO Humanoid for Action and Communication Rodolphe GELIN Aldebaran Robotics 7 th workshop on Humanoid November Soccer 2012 Robots Osaka, November 2012 Overview French National Project labeled by Cluster
More informationSensing and Perception
Unit D tion Exploring Robotics Spring, 2013 D.1 Why does a robot need sensors? the environment is complex the environment is dynamic enable the robot to learn about current conditions in its environment.
More informationROBOTICS ENG YOUSEF A. SHATNAWI INTRODUCTION
ROBOTICS INTRODUCTION THIS COURSE IS TWO PARTS Mobile Robotics. Locomotion (analogous to manipulation) (Legged and wheeled robots). Navigation and obstacle avoidance algorithms. Robot Vision Sensors and
More informationHumanoid robot. Honda's ASIMO, an example of a humanoid robot
Humanoid robot Honda's ASIMO, an example of a humanoid robot A humanoid robot is a robot with its overall appearance based on that of the human body, allowing interaction with made-for-human tools or environments.
More informationSensor system of a small biped entertainment robot
Advanced Robotics, Vol. 18, No. 10, pp. 1039 1052 (2004) VSP and Robotics Society of Japan 2004. Also available online - www.vsppub.com Sensor system of a small biped entertainment robot Short paper TATSUZO
More informationYDDON. Humans, Robots, & Intelligent Objects New communication approaches
YDDON Humans, Robots, & Intelligent Objects New communication approaches Building Robot intelligence Interdisciplinarity Turning things into robots www.ydrobotics.co m Edifício A Moagem Cidade do Engenho
More informationSpace Research expeditions and open space work. Education & Research Teaching and laboratory facilities. Medical Assistance for people
Space Research expeditions and open space work Education & Research Teaching and laboratory facilities. Medical Assistance for people Safety Life saving activity, guarding Military Use to execute missions
More information* Intelli Robotic Wheel Chair for Specialty Operations & Physically Challenged
ADVANCED ROBOTICS SOLUTIONS * Intelli Mobile Robot for Multi Specialty Operations * Advanced Robotic Pick and Place Arm and Hand System * Automatic Color Sensing Robot using PC * AI Based Image Capturing
More informationA Semi-Minimalistic Approach to Humanoid Design
International Journal of Scientific and Research Publications, Volume 2, Issue 4, April 2012 1 A Semi-Minimalistic Approach to Humanoid Design Hari Krishnan R., Vallikannu A.L. Department of Electronics
More informationHaptics CS327A
Haptics CS327A - 217 hap tic adjective relating to the sense of touch or to the perception and manipulation of objects using the senses of touch and proprioception 1 2 Slave Master 3 Courtesy of Walischmiller
More informationBooklet of teaching units
International Master Program in Mechatronic Systems for Rehabilitation Booklet of teaching units Third semester (M2 S1) Master Sciences de l Ingénieur Université Pierre et Marie Curie Paris 6 Boite 164,
More informationNCCT IEEE PROJECTS ADVANCED ROBOTICS SOLUTIONS. Latest Projects, in various Domains. Promise for the Best Projects
NCCT Promise for the Best Projects IEEE PROJECTS in various Domains Latest Projects, 2009-2010 ADVANCED ROBOTICS SOLUTIONS EMBEDDED SYSTEM PROJECTS Microcontrollers VLSI DSP Matlab Robotics ADVANCED ROBOTICS
More informationChapter 1. Robot and Robotics PP
Chapter 1 Robot and Robotics PP. 01-19 Modeling and Stability of Robotic Motions 2 1.1 Introduction A Czech writer, Karel Capek, had first time used word ROBOT in his fictional automata 1921 R.U.R (Rossum
More informationManipulation. Manipulation. Better Vision through Manipulation. Giorgio Metta Paul Fitzpatrick. Humanoid Robotics Group.
Manipulation Manipulation Better Vision through Manipulation Giorgio Metta Paul Fitzpatrick Humanoid Robotics Group MIT AI Lab Vision & Manipulation In robotics, vision is often used to guide manipulation
More informationMajor Project SSAD. Mentor : Raghudeep SSAD Mentor :Manish Jha Group : Group20 Members : Harshit Daga ( ) Aman Saxena ( )
Major Project SSAD Advisor : Dr. Kamalakar Karlapalem Mentor : Raghudeep SSAD Mentor :Manish Jha Group : Group20 Members : Harshit Daga (200801028) Aman Saxena (200801010) We were supposed to calculate
More informationDevelopment of intelligent systems
Development of intelligent systems (RInS) Robot sensors Danijel Skočaj University of Ljubljana Faculty of Computer and Information Science Academic year: 2017/18 Development of intelligent systems Robotic
More informationBuilding Perceptive Robots with INTEL Euclid Development kit
Building Perceptive Robots with INTEL Euclid Development kit Amit Moran Perceptual Computing Systems Innovation 2 2 3 A modern robot should Perform a task Find its way in our world and move safely Understand
More informationTeam Description for Humanoid KidSize League of RoboCup Stephen McGill, Seung Joon Yi, Yida Zhang, Aditya Sreekumar, and Professor Dan Lee
Team DARwIn Team Description for Humanoid KidSize League of RoboCup 2013 Stephen McGill, Seung Joon Yi, Yida Zhang, Aditya Sreekumar, and Professor Dan Lee GRASP Lab School of Engineering and Applied Science,
More informationFeel the beat: using cross-modal rhythm to integrate perception of objects, others, and self
Feel the beat: using cross-modal rhythm to integrate perception of objects, others, and self Paul Fitzpatrick and Artur M. Arsenio CSAIL, MIT Modal and amodal features Modal and amodal features (following
More informationNao Devils Dortmund. Team Description for RoboCup Matthias Hofmann, Ingmar Schwarz, and Oliver Urbann
Nao Devils Dortmund Team Description for RoboCup 2014 Matthias Hofmann, Ingmar Schwarz, and Oliver Urbann Robotics Research Institute Section Information Technology TU Dortmund University 44221 Dortmund,
More informationEE631 Cooperating Autonomous Mobile Robots. Lecture 1: Introduction. Prof. Yi Guo ECE Department
EE631 Cooperating Autonomous Mobile Robots Lecture 1: Introduction Prof. Yi Guo ECE Department Plan Overview of Syllabus Introduction to Robotics Applications of Mobile Robots Ways of Operation Single
More informationKINECT CONTROLLED HUMANOID AND HELICOPTER
KINECT CONTROLLED HUMANOID AND HELICOPTER Muffakham Jah College of Engineering & Technology Presented by : MOHAMMED KHAJA ILIAS PASHA ZESHAN ABDUL MAJEED AZMI SYED ABRAR MOHAMMED ISHRAQ SARID MOHAMMED
More informationHumanoids. Lecture Outline. RSS 2010 Lecture # 19 Una-May O Reilly. Definition and motivation. Locomotion. Why humanoids? What are humanoids?
Humanoids RSS 2010 Lecture # 19 Una-May O Reilly Lecture Outline Definition and motivation Why humanoids? What are humanoids? Examples Locomotion RSS 2010 Humanoids Lecture 1 1 Why humanoids? Capek, Paris
More informationOptic Flow Based Skill Learning for A Humanoid to Trap, Approach to, and Pass a Ball
Optic Flow Based Skill Learning for A Humanoid to Trap, Approach to, and Pass a Ball Masaki Ogino 1, Masaaki Kikuchi 1, Jun ichiro Ooga 1, Masahiro Aono 1 and Minoru Asada 1,2 1 Dept. of Adaptive Machine
More informationFast, Robust Colour Vision for the Monash Humanoid Andrew Price Geoff Taylor Lindsay Kleeman
Fast, Robust Colour Vision for the Monash Humanoid Andrew Price Geoff Taylor Lindsay Kleeman Intelligent Robotics Research Centre Monash University Clayton 3168, Australia andrew.price@eng.monash.edu.au
More informationAuditory Localization
Auditory Localization CMPT 468: Sound Localization Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University November 15, 2013 Auditory locatlization is the human perception
More informationsin( x m cos( The position of the mass point D is specified by a set of state variables, (θ roll, θ pitch, r) related to the Cartesian coordinates by:
Research Article International Journal of Current Engineering and Technology ISSN 77-46 3 INPRESSCO. All Rights Reserved. Available at http://inpressco.com/category/ijcet Modeling improvement of a Humanoid
More informationThe project. General challenges and problems. Our subjects. The attachment and locomotion system
The project The Ceilbot project is a study and research project organized at the Helsinki University of Technology. The aim of the project is to design and prototype a multifunctional robot which takes
More informationFeeding human senses through Immersion
Virtual Reality Feeding human senses through Immersion 1. How many human senses? 2. Overview of key human senses 3. Sensory stimulation through Immersion 4. Conclusion Th3.1 1. How many human senses? [TRV
More informationPlan. Vision Solves Problems. Distal vs. proximal stimulus. Vision as an inverse problem. Unconscious inference (Helmholtz)
The Art and Science of Depiction Vision Solves Problems Plan Vision as an cognitive process Computational theory of vision Constancy, invariants Fredo Durand MIT- Lab for Computer Science Intro to Visual
More informationOmni-Directional Catadioptric Acquisition System
Technical Disclosure Commons Defensive Publications Series December 18, 2017 Omni-Directional Catadioptric Acquisition System Andreas Nowatzyk Andrew I. Russell Follow this and additional works at: http://www.tdcommons.org/dpubs_series
More informationRobot Visual Mapper. Hung Dang, Jasdeep Hundal and Ramu Nachiappan. Fig. 1: A typical image of Rovio s environment
Robot Visual Mapper Hung Dang, Jasdeep Hundal and Ramu Nachiappan Abstract Mapping is an essential component of autonomous robot path planning and navigation. The standard approach often employs laser
More informationE90 Project Proposal. 6 December 2006 Paul Azunre Thomas Murray David Wright
E90 Project Proposal 6 December 2006 Paul Azunre Thomas Murray David Wright Table of Contents Abstract 3 Introduction..4 Technical Discussion...4 Tracking Input..4 Haptic Feedack.6 Project Implementation....7
More informationThe UPennalizers RoboCup Standard Platform League Team Description Paper 2017
The UPennalizers RoboCup Standard Platform League Team Description Paper 2017 Yongbo Qian, Xiang Deng, Alex Baucom and Daniel D. Lee GRASP Lab, University of Pennsylvania, Philadelphia PA 19104, USA, https://www.grasp.upenn.edu/
More informationIntelligent Robotics Sensors and Actuators
Intelligent Robotics Sensors and Actuators Luís Paulo Reis (University of Porto) Nuno Lau (University of Aveiro) The Perception Problem Do we need perception? Complexity Uncertainty Dynamic World Detection/Correction
More informationARTIFICIAL INTELLIGENCE - ROBOTICS
ARTIFICIAL INTELLIGENCE - ROBOTICS http://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_robotics.htm Copyright tutorialspoint.com Robotics is a domain in artificial intelligence
More informationPerception. Introduction to HRI Simmons & Nourbakhsh Spring 2015
Perception Introduction to HRI Simmons & Nourbakhsh Spring 2015 Perception my goals What is the state of the art boundary? Where might we be in 5-10 years? The Perceptual Pipeline The classical approach:
More informationUnit IV: Sensation & Perception. Module 19 Vision Organization & Interpretation
Unit IV: Sensation & Perception Module 19 Vision Organization & Interpretation Visual Organization 19-1 Perceptual Organization 19-1 How do we form meaningful perceptions from sensory information? A group
More informationProbabilistic Robotics Course. Robots and Sensors Orazio
Probabilistic Robotics Course Robots and Sensors Orazio Giorgio Grisetti grisetti@dis.uniroma1.it Dept of Computer Control and Management Engineering Sapienza University of Rome Outline Robot Devices Overview
More informationPRESENTED BY HUMANOID IIT KANPUR
SENSORS & ACTUATORS Robotics Club (Science and Technology Council, IITK) PRESENTED BY HUMANOID IIT KANPUR October 11th, 2017 WHAT ARE WE GOING TO LEARN!! COMPARISON between Transducers Sensors And Actuators.
More informationService Robots in an Intelligent House
Service Robots in an Intelligent House Jesus Savage Bio-Robotics Laboratory biorobotics.fi-p.unam.mx School of Engineering Autonomous National University of Mexico UNAM 2017 OUTLINE Introduction A System
More informationInteractive Simulation: UCF EIN5255. VR Software. Audio Output. Page 4-1
VR Software Class 4 Dr. Nabil Rami http://www.simulationfirst.com/ein5255/ Audio Output Can be divided into two elements: Audio Generation Audio Presentation Page 4-1 Audio Generation A variety of audio
More informationBlind navigation with a wearable range camera and vibrotactile helmet
Blind navigation with a wearable range camera and vibrotactile helmet (author s name removed for double-blind review) X university 1@2.com (author s name removed for double-blind review) X university 1@2.com
More informationVOICE CONTROL BASED PROSTHETIC HUMAN ARM
VOICE CONTROL BASED PROSTHETIC HUMAN ARM Ujwal R 1, Rakshith Narun 2, Harshell Surana 3, Naga Surya S 4, Ch Preetham Dheeraj 5 1.2.3.4.5. Student, Department of Electronics and Communication Engineering,
More informationIntroduction to Robotics
Artificial Intelligence & Neuro Cognitive Systems Fakultät für Informatik Introduction to Robotics Dr.-Ing. John Nassour 11.10.2016 Suggested literature General Information Prerequisites: Basic knowledge
More informationThe UT Austin Villa 3D Simulation Soccer Team 2008
UT Austin Computer Sciences Technical Report AI09-01, February 2009. The UT Austin Villa 3D Simulation Soccer Team 2008 Shivaram Kalyanakrishnan, Yinon Bentor and Peter Stone Department of Computer Sciences
More informationRobot: Robonaut 2 The first humanoid robot to go to outer space
ProfileArticle Robot: Robonaut 2 The first humanoid robot to go to outer space For the complete profile with media resources, visit: http://education.nationalgeographic.org/news/robot-robonaut-2/ Program
More informationRange Sensing strategies
Range Sensing strategies Active range sensors Ultrasound Laser range sensor Slides adopted from Siegwart and Nourbakhsh 4.1.6 Range Sensors (time of flight) (1) Large range distance measurement -> called
More informationUsing Hybrid Reality to Explore Scientific Exploration Scenarios
Using Hybrid Reality to Explore Scientific Exploration Scenarios EVA Technology Workshop 2017 Kelsey Young Exploration Scientist NASA Hybrid Reality Lab - Background Combines real-time photo-realistic
More informationProspective Teleautonomy For EOD Operations
Perception and task guidance Perceived world model & intent Prospective Teleautonomy For EOD Operations Prof. Seth Teller Electrical Engineering and Computer Science Department Computer Science and Artificial
More informationZJUDancer Team Description Paper Humanoid Kid-Size League of Robocup 2014
ZJUDancer Team Description Paper Humanoid Kid-Size League of Robocup 2014 Yu DongDong, Xiang Chuan, Zhou Chunlin, and Xiong Rong State Key Lab. of Industrial Control Technology, Zhejiang University, Hangzhou,
More informationProprioception & force sensing
Proprioception & force sensing Roope Raisamo Tampere Unit for Computer-Human Interaction (TAUCHI) School of Information Sciences University of Tampere, Finland Based on material by Jussi Rantala, Jukka
More informationWhy Humanoid Robots?*
Why Humanoid Robots?* AJLONTECH * Largely adapted from Carlos Balaguer s talk in IURS 06 Outline Motivation What is a Humanoid Anyway? History of Humanoid Robots Why Develop Humanoids? Challenges in Humanoids
More information2. Introduction to Computer Haptics
2. Introduction to Computer Haptics Seungmoon Choi, Ph.D. Assistant Professor Dept. of Computer Science and Engineering POSTECH Outline Basics of Force-Feedback Haptic Interfaces Introduction to Computer
More informationZJUDancer Team Description Paper Humanoid Kid-Size League of Robocup 2015
ZJUDancer Team Description Paper Humanoid Kid-Size League of Robocup 2015 Yu DongDong, Liu Yun, Zhou Chunlin, and Xiong Rong State Key Lab. of Industrial Control Technology, Zhejiang University, Hangzhou,
More informationKI-SUNG SUH USING NAO INTRODUCTION TO INTERACTIVE HUMANOID ROBOTS
KI-SUNG SUH USING NAO INTRODUCTION TO INTERACTIVE HUMANOID ROBOTS 2 WORDS FROM THE AUTHOR Robots are both replacing and assisting people in various fields including manufacturing, extreme jobs, and service
More informationEROS TEAM. Team Description for Humanoid Kidsize League of Robocup2013
EROS TEAM Team Description for Humanoid Kidsize League of Robocup2013 Azhar Aulia S., Ardiansyah Al-Faruq, Amirul Huda A., Edwin Aditya H., Dimas Pristofani, Hans Bastian, A. Subhan Khalilullah, Dadet
More informationHaptic presentation of 3D objects in virtual reality for the visually disabled
Haptic presentation of 3D objects in virtual reality for the visually disabled M Moranski, A Materka Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, Lodz, POLAND marcin.moranski@p.lodz.pl,
More informationRapid Development System for Humanoid Vision-based Behaviors with Real-Virtual Common Interface
Rapid Development System for Humanoid Vision-based Behaviors with Real-Virtual Common Interface Kei Okada 1, Yasuyuki Kino 1, Fumio Kanehiro 2, Yasuo Kuniyoshi 1, Masayuki Inaba 1, Hirochika Inoue 1 1
More informationIVR: Introduction to Control
IVR: Introduction to Control OVERVIEW Control systems Transformations Simple control algorithms History of control Centrifugal governor M. Boulton and J. Watt (1788) J. C. Maxwell (1868) On Governors.
More informationInteracting within Virtual Worlds (based on talks by Greg Welch and Mark Mine)
Interacting within Virtual Worlds (based on talks by Greg Welch and Mark Mine) Presentation Working in a virtual world Interaction principles Interaction examples Why VR in the First Place? Direct perception
More informationEC-433 Digital Image Processing
EC-433 Digital Image Processing Lecture 2 Digital Image Fundamentals Dr. Arslan Shaukat 1 Fundamental Steps in DIP Image Acquisition An image is captured by a sensor (such as a monochrome or color TV camera)
More informationROBOTICS & EMBEDDED SYSTEMS
ROBOTICS & EMBEDDED SYSTEMS By, DON DOMINIC 29 S3 ECE CET EMBEDDED SYSTEMS small scale computers perform a specific task single component(hardware + software)- embedded after design, incapable of changing
More informationProject Number: P13203
Multidisciplinary Senior Design Conference Kate Gleason College of Engineering Rochester Institute of Technology Rochester, New York 14623 Project Number: P13203 TIGERBOT EXTENSION Mohammad Arefin Electrical
More informationJane Li. Assistant Professor Mechanical Engineering Department, Robotic Engineering Program Worcester Polytechnic Institute
Jane Li Assistant Professor Mechanical Engineering Department, Robotic Engineering Program Worcester Polytechnic Institute Use an example to explain what is admittance control? You may refer to exoskeleton
More informationRobot: icub This humanoid helps us study the brain
ProfileArticle Robot: icub This humanoid helps us study the brain For the complete profile with media resources, visit: http://education.nationalgeographic.org/news/robot-icub/ Program By Robohub Tuesday,
More informationKMUTT Kickers: Team Description Paper
KMUTT Kickers: Team Description Paper Thavida Maneewarn, Xye, Korawit Kawinkhrue, Amnart Butsongka, Nattapong Kaewlek King Mongkut s University of Technology Thonburi, Institute of Field Robotics (FIBO)
More informationTelevision Production DDA Review. Post Production
Post Production Post Production Phase During Post, the video is assembled or Edited into the final form for broadcast Music and graphics will be added to support the visuals Voice overs would be added
More informationSitiK KIT. Team Description for the Humanoid KidSize League of RoboCup 2010
SitiK KIT Team Description for the Humanoid KidSize League of RoboCup 2010 Shohei Takesako, Nasuka Awai, Kei Sugawara, Hideo Hattori, Yuichiro Hirai, Takesi Miyata, Keisuke Urushibata, Tomoya Oniyama,
More informationWelcome to this course on «Natural Interactive Walking on Virtual Grounds»!
Welcome to this course on «Natural Interactive Walking on Virtual Grounds»! The speaker is Anatole Lécuyer, senior researcher at Inria, Rennes, France; More information about him at : http://people.rennes.inria.fr/anatole.lecuyer/
More informationCIS 849: Autonomous Robot Vision
CIS 849: Autonomous Robot Vision Instructor: Christopher Rasmussen Course web page: www.cis.udel.edu/~cer/arv September 5, 2002 Purpose of this Course To provide an introduction to the uses of visual sensing
More informationRobot Sensors Introduction to Robotics Lecture Handout September 20, H. Harry Asada Massachusetts Institute of Technology
Robot Sensors 2.12 Introduction to Robotics Lecture Handout September 20, 2004 H. Harry Asada Massachusetts Institute of Technology Touch Sensor CCD Camera Vision System Ultrasonic Sensor Photo removed
More informationDesign and Implementation of a Simplified Humanoid Robot with 8 DOF
Design and Implementation of a Simplified Humanoid Robot with 8 DOF Hari Krishnan R & Vallikannu A. L Department of Electronics and Communication Engineering, Hindustan Institute of Technology and Science,
More informationAPPLICATION OF COMPUTER VISION FOR DETERMINATION OF SYMMETRICAL OBJECT POSITION IN THREE DIMENSIONAL SPACE
APPLICATION OF COMPUTER VISION FOR DETERMINATION OF SYMMETRICAL OBJECT POSITION IN THREE DIMENSIONAL SPACE Najirah Umar 1 1 Jurusan Teknik Informatika, STMIK Handayani Makassar Email : najirah_stmikh@yahoo.com
More informationBaset Adult-Size 2016 Team Description Paper
Baset Adult-Size 2016 Team Description Paper Mojtaba Hosseini, Vahid Mohammadi, Farhad Jafari 2, Dr. Esfandiar Bamdad 1 1 Humanoid Robotic Laboratory, Robotic Center, Baset Pazhuh Tehran company. No383,
More informationAutonomous and Mobile Robotics Prof. Giuseppe Oriolo. Introduction: Applications, Problems, Architectures
Autonomous and Mobile Robotics Prof. Giuseppe Oriolo Introduction: Applications, Problems, Architectures organization class schedule 2017/2018: 7 Mar - 1 June 2018, Wed 8:00-12:00, Fri 8:00-10:00, B2 6
More informationIntroduction to Haptics
Introduction to Haptics Roope Raisamo Multimodal Interaction Research Group Tampere Unit for Computer Human Interaction (TAUCHI) Department of Computer Sciences University of Tampere, Finland Definition
More information23270: AUGMENTED REALITY FOR NAVIGATION AND INFORMATIONAL ADAS. Sergii Bykov Technical Lead Machine Learning 12 Oct 2017
23270: AUGMENTED REALITY FOR NAVIGATION AND INFORMATIONAL ADAS Sergii Bykov Technical Lead Machine Learning 12 Oct 2017 Product Vision Company Introduction Apostera GmbH with headquarter in Munich, was
More informationOverview of current developments in haptic APIs
Central European Seminar on Computer Graphics for students, 2011 AUTHOR: Petr Kadleček SUPERVISOR: Petr Kmoch Overview of current developments in haptic APIs Presentation Haptics Haptic programming Haptic
More informationATLAS. High Mobility, Humanoid Robot ROBOT 17 ALLSTARS -
ATLAS High Mobility, Humanoid Robot Position: High Mobility, Humanoid Robot ATLAS Coach: Marc Raibert Stats: High mobility, humanoid robot designed to negotiate outdoor, rough terrain; Atlas can walk bipedally,
More informationDEVELOPMENT OF A HUMANOID ROBOT FOR EDUCATION AND OUTREACH. K. Kelly, D. B. MacManus, C. McGinn
DEVELOPMENT OF A HUMANOID ROBOT FOR EDUCATION AND OUTREACH K. Kelly, D. B. MacManus, C. McGinn Department of Mechanical and Manufacturing Engineering, Trinity College, Dublin 2, Ireland. ABSTRACT Robots
More informationCognitive robots and emotional intelligence Cloud robotics Ethical, legal and social issues of robotic Construction robots Human activities in many
Preface The jubilee 25th International Conference on Robotics in Alpe-Adria-Danube Region, RAAD 2016 was held in the conference centre of the Best Western Hotel M, Belgrade, Serbia, from 30 June to 2 July
More informationNatural Interaction with Social Robots
Workshop: Natural Interaction with Social Robots Part of the Topig Group with the same name. http://homepages.stca.herts.ac.uk/~comqkd/tg-naturalinteractionwithsocialrobots.html organized by Kerstin Dautenhahn,
More informationTraining NAO using Kinect
Training NAO using Kinect Michalis Chartomatsidis, Emmanouil Androulakis, Ergina Kavallieratou University of the Aegean Samos, Dept of Information & Communications Systems, Greece kavallieratou@aegean.gr
More informationAdvanced Distributed Architecture for a Small Biped Robot Control M. Albero, F. Blanes, G. Benet, J.E. Simó, J. Coronel
Advanced Distributed Architecture for a Small Biped Robot Control M. Albero, F. Blanes, G. Benet, J.E. Simó, J. Coronel Departamento de Informática de Sistemas y Computadores. (DISCA) Universidad Politécnica
More informationLimits of a Distributed Intelligent Networked Device in the Intelligence Space. 1 Brief History of the Intelligent Space
Limits of a Distributed Intelligent Networked Device in the Intelligence Space Gyula Max, Peter Szemes Budapest University of Technology and Economics, H-1521, Budapest, Po. Box. 91. HUNGARY, Tel: +36
More informationSensation and Perception
Page 94 Check syllabus! We are starting with Section 6-7 in book. Sensation and Perception Our Link With the World Shorter wavelengths give us blue experience Longer wavelengths give us red experience
More informationTeam Description Paper: HuroEvolution Humanoid Robot for Robocup 2014 Humanoid League
Team Description Paper: HuroEvolution Humanoid Robot for Robocup 2014 Humanoid League Chung-Hsien Kuo, Yu-Cheng Kuo, Yu-Ping Shen, Chen-Yun Kuo, Yi-Tseng Lin 1 Department of Electrical Egineering, National
More informationCOMS W4172 Design Principles
COMS W4172 Design Principles Steven Feiner Department of Computer Science Columbia University New York, NY 10027 www.cs.columbia.edu/graphics/courses/csw4172 January 25, 2018 1 2D & 3D UIs: What s the
More informationPSU Centaur Hexapod Project
PSU Centaur Hexapod Project Integrate an advanced robot that will be new in comparison with all robots in the world Reasoning by analogy Learning using Logic Synthesis methods Learning using Data Mining
More informationControlling Humanoid Robot Using Head Movements
Volume-5, Issue-2, April-2015 International Journal of Engineering and Management Research Page Number: 648-652 Controlling Humanoid Robot Using Head Movements S. Mounica 1, A. Naga bhavani 2, Namani.Niharika
More informationTeam Description Paper: HuroEvolution Humanoid Robot for Robocup 2010 Humanoid League
Team Description Paper: HuroEvolution Humanoid Robot for Robocup 2010 Humanoid League Chung-Hsien Kuo 1, Hung-Chyun Chou 1, Jui-Chou Chung 1, Po-Chung Chia 2, Shou-Wei Chi 1, Yu-De Lien 1 1 Department
More information2 Focus of research and research interests
The Reem@LaSalle 2014 Robocup@Home Team Description Chang L. Zhu 1, Roger Boldú 1, Cristina de Saint Germain 1, Sergi X. Ubach 1, Jordi Albó 1 and Sammy Pfeiffer 2 1 La Salle, Ramon Llull University, Barcelona,
More informationIntroduction to Vision & Robotics
Introduction to Vision & Robotics by Bob Fisher rbf@inf.ed.ac.uk Introduction to Robotics Introduction Some definitions Applications of robotics and vision The challenge: a demonstration Historical highlights
More informationAn Introduction To Modular Robots
An Introduction To Modular Robots Introduction Morphology and Classification Locomotion Applications Challenges 11/24/09 Sebastian Rockel Introduction Definition (Robot) A robot is an artificial, intelligent,
More informationROBOT VISION. Dr.M.Madhavi, MED, MVSREC
ROBOT VISION Dr.M.Madhavi, MED, MVSREC Robotic vision may be defined as the process of acquiring and extracting information from images of 3-D world. Robotic vision is primarily targeted at manipulation
More informationCIT Brains (Kid Size League)
CIT Brains (Kid Size League) Yasuo Hayashibara 1, Hideaki Minakata 1, Kiyoshi Irie 1, Taiki Fukuda 1, Victor Tee Sin Loong 1, Daiki Maekawa 1, Yusuke Ito 1, Takamasa Akiyama 1, Taiitiro Mashiko 1, Kohei
More informationCS277 - Experimental Haptics Lecture 2. Haptic Rendering
CS277 - Experimental Haptics Lecture 2 Haptic Rendering Outline Announcements Human haptic perception Anatomy of a visual-haptic simulation Virtual wall and potential field rendering A note on timing...
More informationSensing. Autonomous systems. Properties. Classification. Key requirement of autonomous systems. An AS should be connected to the outside world.
Sensing Key requirement of autonomous systems. An AS should be connected to the outside world. Autonomous systems Convert a physical value to an electrical value. From temperature, humidity, light, to
More information