everything you always wanted to know about @home league, but … · 2019-09-16 · everything you...

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Everything you always wanted to know about @home league, but were afraid to ask Prof. Dr. Paul G. Plöger, (Team b-it-bots) Dirk Holz, Uni Bonn, (Team Nimbro) Sven Wachsmuth, Uni Bielefeld (Team Tobi) Bonn-Rhein-Sieg University

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Page 1: Everything you always wanted to know about @home league, but … · 2019-09-16 · Everything you always wanted to know about @home league, but were afraid to ask Prof. Dr. Paul G

Everything you always wanted to know about @home league, but were afraid to ask Prof. Dr. Paul G. Plöger, (Team b-it-bots) Dirk Holz, Uni Bonn, (Team Nimbro) Sven Wachsmuth, Uni Bielefeld (Team Tobi)

Bonn-Rhein-Sieg University

Page 2: Everything you always wanted to know about @home league, but … · 2019-09-16 · Everything you always wanted to know about @home league, but were afraid to ask Prof. Dr. Paul G

2

Prof. Dr.

Paul G. Plöger Computer

Science Bonn-Rhein-Sieg University oas

BRSU: University of Applied Science founded in 1995

capital moved from Bonn to Berlin 7500 students, 145 tenure prof, 466 staff

Key concepts: international relations family oriented excellence in (industrial) applications

BRSU projects: past: soccer playing robots (Middle Size League, internal) current: student team in service robotics (Robocup@home, internal) current: learning robots XPERO: EU funds,

BRICS: EU funds, GRRI: BMBF, German, Russian cooperation

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3

Prof. Dr.

Paul G. Plöger Computer

Science Bonn-Rhein-Sieg University oas

Service Robotics Q&A:

How did it all start? => My short history of b-it-bots + MAS projects.

How to make a robot aware? => Face and gesture recognition

What is this? => Perception, obj cat+free text

Pass it over! => Grasp, manipl.

How to do component cooperation? => Architecture

What cannot be done => The Limits of control

What do we aim for with all this?

What is Robocup@home all about?

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Prof. Dr.

Paul G. Plöger Fachbereich

Informatik Hochschule

Bonn-Rhein-Sieg 4

IROS, 2012 San Francisco

B-it-bots roboter Jenny performing some common household tasks

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ROBOCUP@home : a test bed for service robots => parts of the contest:

Manipulation and Object recognition���place-it, find-it, identify-it, grasp-it, comment-about

Navigation���(re)plan-path, open-door, comment-about

General Purpose Service Robot���navigate-to, (re)plan-path, listen-to, find-it, identify-it, grasp-it, talk-to, reason-about

Person recognition���find-person(s), identify-person, identify-pose

Speech Rec. and sound loc.���localize-sound, talk-to, reason-about

Open Challenge

Masters in Autonomous Systems

Bonn-Rhein-Sieg Uni. Appl.Science Paul G. Plöger

These unified tests allow BENCHMARKING of different behavior systems

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All tests���are mere���Use cases !���

Masters in Autonomous Systems

Bonn-Rhein-Sieg Uni. Appl.Science Paul G. Plöger

Behaviour complexity:���sequence of nested/ hierachical FSMs

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Use cases => necessary abilities of an autonomous Service Robot

• Speech i/o (“Yes, No! What ?!”)

• Object recognition and identification (“Which?”)

• Grasping of objects (“Get !”)

• Locomotion (“Go !”)

• Navigation ( “Where am I ?”)

• Person identification (“Who are you?”)

Masters in Autonomous Systems

Bonn-Rhein-Sieg Uni. Appl.Science Paul G. Plöger

} Choose and���Integrate !!!!

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necessary abilities of an autonomous Service Robot, best in class….

•  Speech => Loquendo (win)+Leopard (MacOS)

• Object recognition => RGB-D linemod (linux)

• Grasping of objects => KUKA Native lib (linux)

•  Locomotion => Indiveri path follower (linux)

• Navigation => home grown MS thesis (Dirk Holz)(linux)

•  Person identification => L1identity Sol. (win)

Masters in Autonomous Systems

Bonn-Rhein-Sieg Uni. Appl.Science Paul G. Plöger

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RS232 USB2 TCP/IP 1394/400 analog

Goal: Middleware for a Cognitive System

Human Interface

Manipulation + Face Recognition Locomotion + Navigation

Sequencer + Speech Synthesis

Motor control Laser

Linux

Mac OS

MS Win

MS Win

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Data + Control flow���when grasping

•  Components offer high level commands == services

•  Scheduler command “Grasp”

•  All realtime aspects / and loops inside each component

•  pan / tilt loop

•  Point to point movements

•  ICE middleware for integration

Adapted���SIFT

Color Blob���tracker

2D -> 3D���pose

KUKA native interface

Scheduler

Disparity

grasp ID

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Different HW approaches Industrial man. Care-O-bot-3,���Payload: ���~10 Kg (!)

Ergonomy ���(2 sides/faces)

nice user-friendly design

Enabled for every day use

Reliability (KUKA components)

Final goal fault rob./ recovery

Selfmade => exact match of functionality Lightweight, omni wheels moving shoulder over a spine centralized CPU

Dynamaid, an Anthropomorphic Robot for Research on Domestic���Service Applications, Jörg Stückler, Sven Behnke ECMR’09, 2010

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Bonn-Rhein-Sieg Uni. Appl.Science Benchmarking

2876  

3597  

5300  

3322  

2080  1888  

2780  

1434  

2876   2850  

3250  

2050  

2322  

997  844  

389  

0  

1000  

2000  

3000  

4000  

5000  

6000  

2010   2011   2012   2013  

@home  Punkte:  Entwicklung  über  die  Jahre  2010-­‐2013  

STAGE1  max  

STAGE1  mean  

STAGE2  Max    

STAGE2  Mean  

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Bonn-Rhein-Sieg Uni. Appl.Science Benchmarking

Dirk Holz, et.al: On RoboCup@Home - Past, Present and Future of a Scientic Competition for Service Robots���to be published

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Research topics on robot abilities

Furniture recognition

Door detection

Event recognition

Detecting the opening of a door Thanks to Sven Wachsmuth, Uni Bielefeld

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Thanks to Sven Wachsmuth, Uni Bielefeld

Emergency situation

Restaurant

Follow me

Cocktail Party

Basic Functionality Follow me

Page 16: Everything you always wanted to know about @home league, but … · 2019-09-16 · Everything you always wanted to know about @home league, but were afraid to ask Prof. Dr. Paul G

http://www.robocupathome.org/

Eindhoven, The Netherlands, 2013

@home league, RoboCup 2013, Eindhoven NEXT: RoboCup 2016, Leipzig, 30.6. - 4.7.2016 IFAC 9th Symposium Intelligent Autonomous Vehicles, iav2016.inf.h-brs.de

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17

Prof. Dr.

Paul G. Plöger Computer

Science Bonn-Rhein-Sieg University oas

Résumé Service robotics is catching up to the expectations as implemented in

us by Hollywood as long as movie making industries is taking more advantage of the

HW enhancements then A.I. we will lag behind .. in dedicated niches (3D sensing, environment modeling, scene

understanding, motion control) there is some big momentum though…

… and BTW: true autonomy is still unwanted….

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Prof. Dr.

Paul G. Plöger Computer

Science Bonn-Rhein-Sieg University oas

http://www.b-it-bots.de http://www.iais.fraunhofer.de

http://www.inf.h-bonn-rhein-sieg.de

The Golem: How He Came Into the World, Paul Wegener,1920 Terminator II-Judgement Day, James Cameron, 1991 2001: A Space Odyssey, Stanley Kubrick, 1968 Blade Runner, Ridley Scott, 1982 Metropolis, Fritz Lang, 1927 The Bicentennial Man, Chris Columbus (based on Asimov), 2000

Journal of Intelligent & Robotic Systems Johnny: An Autonomous Service Robot for Domestic Environments Thomas Breuer, Geovanny R. Giorgana Macedo, Ronny Hartanto, Nico Hochgeschwender, Dirk Holz, Frederik Hegger, Zha Jin, Christian Müller, Jan Paulus und Michael Reckhaus, et al. http://www.springerlink.com/content/78311w5vn73p6741/

Answers to films / web links

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Prof. Dr.

Paul G. Plöger Computer

Science Bonn-Rhein-Sieg University oas 19