Intelligent Humanoid Robot

Similar documents
RoboCup. Presented by Shane Murphy April 24, 2003

The State of the Art in Robotics: RoboCup, Rescue, Entertainment, and More

Keywords: Multi-robot adversarial environments, real-time autonomous robots

FU-Fighters. The Soccer Robots of Freie Universität Berlin. Why RoboCup? What is RoboCup?

Hierarchical Controller for Robotic Soccer

Courses on Robotics by Guest Lecturing at Balkan Countries

CORC 3303 Exploring Robotics. Why Teams?

GermanTeam The German National RoboCup Team

Content. 3 Preface 4 Who We Are 6 The RoboCup Initiative 7 Our Robots 8 Hardware 10 Software 12 Public Appearances 14 Achievements 15 Interested?

RoboCup Rescue - Robot League League Talk. Johannes Pellenz RoboCup Rescue Exec

Hierarchical Case-Based Reasoning Behavior Control for Humanoid Robot

Learning and Using Models of Kicking Motions for Legged Robots

SPQR RoboCup 2016 Standard Platform League Qualification Report

CS343 Introduction to Artificial Intelligence Spring 2012

CS343 Introduction to Artificial Intelligence Spring 2010

S.P.Q.R. Legged Team Report from RoboCup 2003

A Vision Based System for Goal-Directed Obstacle Avoidance

SPQR RoboCup 2014 Standard Platform League Team Description Paper

RoboCup was created in 1996 by a group of Japanese,

Baset Adult-Size 2016 Team Description Paper

Introduction to Multi-Agent Programming

Using Reactive and Adaptive Behaviors to Play Soccer

Robotic Systems ECE 401RB Fall 2007

Optic Flow Based Skill Learning for A Humanoid to Trap, Approach to, and Pass a Ball

Multi-Platform Soccer Robot Development System

RoboCup: Not Only a Robotics Soccer Game but also a New Market Created for Future

Overview Agents, environments, typical components

Task Allocation: Role Assignment. Dr. Daisy Tang

Autonomous Robot Soccer Teams

Learning and Using Models of Kicking Motions for Legged Robots

CS295-1 Final Project : AIBO

CMDragons 2009 Team Description

Growing up with Robots Costa MFM and Fernandes JF

EE631 Cooperating Autonomous Mobile Robots. Lecture 1: Introduction. Prof. Yi Guo ECE Department

The Dutch AIBO Team 2004

A Lego-Based Soccer-Playing Robot Competition For Teaching Design

Nao Devils Dortmund. Team Description for RoboCup Matthias Hofmann, Ingmar Schwarz, and Oliver Urbann

How Students Teach Robots to Think The Example of the Vienna Cubes a Robot Soccer Team

Advanced Robotics Introduction

Chapter 31. Intelligent System Architectures

Berlin United - NaoTH 2014

IRH 2017 / Group 10. Hosen Gakuen High School Risu inter. Takeru Saito, Akitaka Fujii. Theme3 Most advanced technologies of robots

* Intelli Robotic Wheel Chair for Specialty Operations & Physically Challenged

Dutch Nao Team. Team Description for Robocup Eindhoven, The Netherlands November 8, 2012

Advanced Robotics Introduction

ROBOTIC SOCCER: THE GATEWAY FOR POWERFUL ROBOTIC APPLICATIONS

NTU Robot PAL 2009 Team Report

Nao Devils Dortmund. Team Description for RoboCup Stefan Czarnetzki, Gregor Jochmann, and Sören Kerner

NCCT IEEE PROJECTS ADVANCED ROBOTICS SOLUTIONS. Latest Projects, in various Domains. Promise for the Best Projects

Outline. Agents and environments Rationality PEAS (Performance measure, Environment, Actuators, Sensors) Environment types Agent types

Find Kick Play An Innate Behavior for the Aibo Robot

NAO-Team Humboldt 2010

Past Progress Brings Us Towards a Research Road Map for Further Competitions and Developments

Multi Robot Localization assisted by Teammate Robots and Dynamic Objects

Humanoid Robot NAO: Developing Behaviors for Football Humanoid Robots

Planning in autonomous mobile robotics

AGENT PLATFORM FOR ROBOT CONTROL IN REAL-TIME DYNAMIC ENVIRONMENTS. Nuno Sousa Eugénio Oliveira

The UT Austin Villa 3D Simulation Soccer Team 2008

EDUCATIONAL ROBOTICS' INTRODUCTORY COURSE

COMP9414/ 9814/ 3411: Artificial Intelligence. Week 2. Classifying AI Tasks

Representation Learning for Mobile Robots in Dynamic Environments

COMP219: Artificial Intelligence. Lecture 2: AI Problems and Applications

RoboCup TDP Team ZSTT

Cognitive Robotics. Behavior Control. Hans-Dieter Burkhard June 2014

Artificial Intelligence: Definition

Behaviour-Based Control. IAR Lecture 5 Barbara Webb

Foundations of Artificial Intelligence

NimbRo 2005 Team Description

Distributed, Play-Based Coordination for Robot Teams in Dynamic Environments

Artificial Intelligence: Implications for Autonomous Weapons. Stuart Russell University of California, Berkeley

Behavior generation for a mobile robot based on the adaptive fitness function

UChile Team Research Report 2009

World Technology Evaluation Center International Study of Robotics Research. Robotic Vehicles. Robotic vehicles study group:

ZJUDancer Team Description Paper

Multi-Fidelity Robotic Behaviors: Acting With Variable State Information

Technical issues of MRL Virtual Robots Team RoboCup 2016, Leipzig Germany

Extra Curricula. Robotics

ECE 517: Reinforcement Learning in Artificial Intelligence

Why Humanoid Robots?*

Front Digital page Strategy and Leadership

Multi Robot Object Tracking and Self Localization

Prof. Emil M. Petriu 17 January 2005 CEG 4392 Computer Systems Design Project (Winter 2005)

The UT Austin Villa 3D Simulation Soccer Team 2007

CS8678_L1. Course Introduction. CS 8678 Introduction to Robotics & AI Dr. Ken Hoganson. Start Momentarily

Robotics Introduction Matteo Matteucci

Does JoiTech Messi dream of RoboCup Goal?

ZJUDancer Team Description Paper Humanoid Kid-Size League of Robocup 2015

1 The Challenge of Robotic Soccer

A Multidisciplinary Approach to Cooperative Robotics

Team Description Paper: Darmstadt Dribblers & Hajime Team (KidSize) and Darmstadt Dribblers (TeenSize)

AC : A KICKING MECHANISM FOR A SOCCER-PLAYING ROBOT: A MULTIDISCIPLINARY SENIOR DESIGN PROJECT

Artificial Intelligence & Robotics from RoboCup to Everyday Applications

Team Playing Behavior in Robot Soccer: A Case-Based Reasoning Approach

CS 730/830: Intro AI. Prof. Wheeler Ruml. TA Bence Cserna. Thinking inside the box. 5 handouts: course info, project info, schedule, slides, asst 1

RoboCup 2012 Best Humanoid Award Winner NimbRo TeenSize

Team-NUST. Team Description for RoboCup-SPL 2014 in João Pessoa, Brazil

What will the robot do during the final demonstration?

LEVELS OF MULTI-ROBOT COORDINATION FOR DYNAMIC ENVIRONMENTS

Hierarchical Reactive Control for Soccer Playing Humanoid Robots

Artificial Intelligence for Games

Transcription:

Intelligent Humanoid Robot Prof. Mayez Al-Mouhamed 22-403, Fall 2007 http://www.ccse.kfupm,.edu.sa/~mayez Computer Engineering Department King Fahd University of Petroleum and Minerals 1

RoboCup : Goal By the year 2050, develop a team of fully autonomous humanoid robots that can win against the human world soccer champion team. More than 3000 researchers from about 35 countries / regions. The RoboCup Federation: a Non Profit Organization registered in Switzerland. National Committees in more than 10 countries. Supporting conferences and coordinating research with industry and related government organization. 2

Can we accomplish the goal? Apollo Project Dream: Send men to the moon and safely return them to the earth. Technologies: systems science, electronics, aviation, project management, etc. First Airplane and fifty years later a man landed on the moon! 3

Computer Chess ENIAC 1946 Deep Blue Computer Chess Dream: to develop a computer that can beat human chess champion. Technologies: Search algorithms, parallel computing, parallel compuer architectures, etc. Effects: Basic computer algorithms, parallel programming, etc. 1997 4

Discovery of DNA and 50 years later the Completion of genome analysis 5

What is RoboCup? RoboCup is like the Apollo Project in the 21st century. By achieving a landmark : to develop a humanoid robot team which can compete with human soccer champion team in 50 years, by the year 2050, realize a new era in which robots truly contribute to human society. 6

The RoboCup Federation RoboCupSoccer Simulation League (2D, 3D) Small Robot League (F-180) Middle Size Robot League (F- 2000) Sony 4-Legged Robot League Humanoid League RoboCupRescue Rescue Simulation League Rescue Robot League RoboCupJunior Soccer Rescue Dance 7

International project holding annual world championship to promote joint research of artificial intelligence and robotics with the subject of football by fully-autonomous robots - History of RoboCup Championships - 1997: 1st in Nagoya, Japan 1998: 2nd in Paris, France 1999: 3rd in Stockholm, Sweden 2000: 4th in Melbourne, Australia 2001: 5th in Seattle, USA 2002: 6th in Fukuoka, Japan 2003: 7th in Padua, Italy 2004: 8th in Lisbon, Portugal 2005: 9th in Osaka, Japan 2006: 10th in Bremen, Germany 8

Application of RoboCup technologies Disaster rescue Intelligent Traffic Systems (ITS) Deep space exploration Office robots Distributed agents RoboCup : Activities RoboCupSoccer Research project using soccer RoboCupJunior International education project using robots RoboCupRescue Disaster rescue system research 9

Robocup Leagues Humanoid League Official league of humanoid robots in which those can do penalty kick, walking, free performance and so on. Expected to be a core league in the near future. Small-sized League Soccer by 5 vs. 5 wheel robots within 15 cm diameter with orange golf ball in the table tennis sized court. Sony 4 legged League League utilizing 4 specially-programmed SONY AIBO Simulation League 11 virtual robots with AI program play soccer games in the field on the server. Remote participation is possible from anywhere. Middle-sized League Soccer by 4 vs. 4 wheel robots within 45 cm diameter with an orange indoor soccer ball in 9x5 m field. 10

Some Robocup Leagues Legged Robot League Small-sized League Middle-sized League Humanoid League 11

Humanoid League 1. Standing on one leg 2. Walking Walk the distance 5 times of the robot height. 3. Penalty Kick 40cm, 80cm and 120cm classes. 5 goals per team. 4. Free Style 5 minutes free demonstration 12

RoboCup Drives Research in Control algorithms, Machine vision, sensing and localization, Real-time distributed computing, Real-time ad hoc networking, Mechanical design, Machine learning, and Autonomous multiagent systems 13

Why RoboCup? A Landmark Project Challenging goal and spill-over of technolgoies Outcome-based A platform for project-oriented education in science and technology A standard problem for AI and robotics. 14

Why This New Course? Robocup matured experience (Germany, Japan, Iran, USA, etc.) Long: since 1996 Diversified: simulation, small-size, Sony 4-legged Hard work, frustration, fun, struggle, success A LOT learned on: Creating teams of completing intelligent robots. 15

Expanding the experience to highschool RoboCup phenomenon started at the primary and secondary school-age levels will prove to be of excellent educational value at the undergraduate level. Education and social aspects contests were held in a public space, students were encouraged to invite their friends to come and watch, other faculty members also came to observe Moral: he excitement of the crowd and the visibility of the event motivated students to work harder after the first (maze) contest in preparing for the second (soccer) contest. 16

Motivation Tournaments are being organized using the robots, and the energy, enthusiasm, and motivation displayed by students is unsurpassed. Learning Objective The ability to demonstrate theoretical models and complex algorithms with a hands-on, accessible medium, strengthens the learning experience for students RoboCup Educational Level Adv. undergraduate and early graduate courses, a repository of curricular materials, replicate and expand others efforts. Advanced Learning Tool Empirically witnessed increased excitement, interest, and motivation of the students, need to formalize these observations with a scientific study of the RoboCup learning environment. 17

Autonomous Robot Perception Cognition Action Sensors Actuators External World 18

19

Autonomy I. Perception sensing, modeling of the world II. Cognition behaviors, action selection, planning, learning multi-robot coordination, teamwork response to opponent, multi-agent learning III. Action motion, navigation, obstacle avoidance 20

Autonomous Robots The basic software architecture 21

I - Action: Motion Four-legged walking Head motion Turning, kicking 22

The Problem of Body Movements How to walk, jump and run? How to kick and dribble? How to stand up? 23

The Problem of Body Movements Modeling Motions Which angles are useful? Complex Calculations: Direct (given angles compute position) Indirect (given position compute angles) How can humans walk? without knowing physics and calculations? 24

II - Perception: sensing for a better perception Perception by Humans (Integration) Perception by Humans (Interpretation) : Competing interpretations Belief_new := update (Perception, Belief_old); 25

Perception: vision Real-time and robust Effective calibration Colored blobs identified as objects Confidence computed 26

Robot Perception Example of image processing and features extraction of the ball: Acquire, segmentation, blob detection, and Ball extraction. 27

The Problem of Perception Example of image processing and features extraction of several colors: original, quantized, main colors, and recognition. 28

Perception := sense(sensorydata); 29

How to Understand the World Perception means interpretation by integration of Old perceptions Data from different sensors Objects identified from recent percepts Knowledge about the world All information is incomplete and unreliable. But: Many redundancies can be exploited using methods from statistics and constraint satisfaction. Exploiting Redundancy Where am I? Where is the ball? 30

Exploiting Redundancy The size of the goal defines a circle of possible positions of the observer 31

Exploiting Redundancy The size of the ball defines a circle of possible positions of the ball relative to the observer 32

Exploiting Redundancy The ball lies on a line before the penalty border line 33

Exploiting Redundancy The ball lies on a line between goal post and observer 34

Exploiting Redundancy Combination yields 2 possible positions 35

Exploiting Redundancy Combination yields 2 possible positions 36

III - Cognition: Behaviors How to Understand the World Parts of a Dialog with the ITA: Customer: Would like to travel. Next month during vacations Yes, swimming is ok. nice picture Want to see other people No, don t like such rocks. Warm water is important for my children good food Information is incomplete and unreliable. Integration from different sources is useful (sensor fusion) Understand the World How to Understand Myself (cognitive) How to use the body? How to stand up, walk, jump and run? (control) How to kick and dribble? (decision) When to perform a double pass? (cooperation) 37

Further Questions: How to Play Where am I? (self-localization vs landmarks) Where is the ball? (localization) Where are the others? What are they doing? What shall I do? How to Play: Belief: What is the state of the world Desires: What are my wishes Intention: Which desires will I realize Plans: How can I realize my intentions Models for beliefs, goals, intentions plans (Agent Oriented Techniques): Program structure for agents/robots Models of partners/opponents in the program Models of others: What are their beliefs/desires/intentions/plans 38

Three different situations at RoboCup (2006): (a) Dribbling challenge (b) Goalkeeper (c) Ball Search 39

Behaviors not see ball Recover timeout Score not see ball not see ball Search next to ball not next to ball Approach see ball 40

Arbiter in context environment. 41

The finite state machine implemented in RobotCore controlling the behavior of the soccer robot. 42

Programming Soccer Robots What can we learn? How to understand the world. How to realize rational behavior in the daily world. It is not really important, if robots will win in 2050... 43

Machine Learning Use trial and error. Evolutionary Algorithms Reinforcement Learning Case Based Reasoning Neural Networks http://www.robocup.de/at- Humboldt/simloid-evo.shtml?de Proprioception: Feeling the own Body 44

AUTONOMOUS ROBOTICS Syllabus Actuator and control Motion and Kinematics Sensing and vision Intelligent Behaviors Bahvior Programming Localization Complex behaviors Robocup simulator (project) 45

Resources and Readings Readings and videos are available at: http://www.cs.cmu.edu/~coral http://www.robocup.org The OpenR Web page has a lot of information: http://openr.aibo.com API for the AIBOs: http://www.cs.cmu.edu/~tekkotsu 46

Thanks to RoboCup Federation RoboCup Teams all over the world Mr. Rida Hasanain, Mr. Salam Ahmad Rifai and all COE Robocup team Sponsors Sony, Empolis, DaimlerChrysler, PSI, WISTA, Gerry Weber, Vivico Hans-Dieter Burkhard, Humboldt-Universität zu Berlin, Institut für Informatik. Professor Peter Stone, Trustee, The RoboCup Federation, Computer Sciences, the Univ. Texas at Austin. Prof. Manuela Veloso, Computer Science Department, CMU. Dr. Thomas Röfer, Breman University, Germany. Dr. E. SKLAR, Brooklyn College, City Univ. of New York A light software architecture for a Humanoid Soccer Robot, A. Maggi et al., IAS-Lab, Dep. of Information Engineering, University of Padua, Italy 47