Design of Intelligent Robotics · RoboEarth •How to deal with a complex world? • Changing scenes • Many possible scenarios 12-03-2010 PAGE 11 •RoboEarth – learning and memorization

Design of Intelligent Robotics

René van de Molengraft

December, 6th, 2010

Theme

/ faculteit werktuigbouwkunde PAGE 211-12-2009

• Health: Care and Cure

Mission


• Help elderly people to stay in their homes• Improve quality of surgery for surgeon and patient

Research challenges


Learning• Low-level:

3D-sensing, world modeling, grasping, locomotion• High-level:

cognition, planning, coordination of multiple robots

Approach• Mixed Model/Data-based• Use priors

Robocup@Home


RoboCup use cases


Midsize league soccer• Scenario: structured, but highly dynamic• Low-level: world modeling, skills• High-level: strategy, coordination

@Home league• Scenario: static, but highly unstructured• Low-level: 3D-sensing, object recognition, grasping• High-level: cognition, learning

RoboEarth Project

• Four-year funding from European Commission (FP7)

• Starting date: December 1st, 2009

• Consortium consisting of:

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Motion Control

• Performance• 90% feedforward

• 10% feedback

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• Humans in day2day tasks• 90% feedforward – learning and memorization

• 10% feedback – sensory feedback

Industrial robots

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• Structured environment• Same scene, same task• No humans

Domestic and care robots

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• How to deal with a complex world?• Changing scenes• Many possible scenarios

RoboEarth

• How to deal with a complex world?• Changing scenes

• Many possible scenarios

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• RoboEarth – learning and memorization

• Share any reusable knowledge between robots

• World-Wide-Web for and by robots

RoboEarth

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Safety and risks

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• Consistency of data in RoboEarth

• Who is allowed to sharing what?

• Use existing protocols (HTTPS)

• Protect “personal” data (compare Streetview)

• Certified users

• Log and analyse usage

• Liability in case of malfunction?

• Autonomous operation

• Who is responsible?

/ faculteit werktuigbouwkunde

• “By the year 2050, develop a team of fully autonomous humanoid robots that can win against the human world soccer champion team”

• Joint development of technology in robotics and artificial intelligence

• Since 1997

Robocup


• Founded spring 2005

• 20 active members

• 2nd place World Cup 2008/2009/2010

Tech United


• fully autonomous

• vision and localisation

• fast and safe

• ball-handling (don’t clamp!)

• ball-kick

• team-play

Challenges


• design a team of autonomous soccer robots

• robot is of DH/CS type

• team is of DH/DS type

• soccer = strategy + skills

Design goal


• robustness

• performance

• time-to-next-tournament

• safety

• maintenance

•

• cost

Design criteria


• FIFA rules

• additional Robocup rules

• size, weight, color

Constraints


• manage complexity

• keep it simple

• hierarchy

• make choices explicit

• use models

• create robustness

• redundancy

Design rules of thumb


team

robot robot robot

Bottom-up design


• localisation

• soccer skills

• intercept, dribble, kick

• soccer roles

• attacker, defender, goalkeeper

• soccer tactics

• pass, assist, play system

Requirements


• low level (hardware) functions

• drive

• kick

• ball handling

• sense environment

• (high) level (sofware) functions

• localisation

• skills

• roles and strategy

Identify functions


HW

HW

HW

HW

HW/SW

HW/SW

HW/SW

HW/SW

SW SW

SW

SW

HW HW HW

HW/SW HW/SW HW/SW

SW SW

SW

SW

HW/SW

HW

System architecture


• which sensors?

• vision

• odometry

• accelerometers

• laser

• hardware or software?

• cpu power

• sensor fusion

Design space exploration


• vision

• number of cameras, type of camera, resolution, omnivision, mirror, construction, acquisition, feature extraction, modelfit, object tracking etc.

Localization


• Interdisciplinary

• mechanics

• electronics

• software

• Approach

• model-based design (simulation and prototyping )

• early integration

Specialists needed




• hardware

• omnivision camera+mirror

• electronic compass

• odometry with motor encoders

• software

• white-line detection

• orientation calibration

• sensor fusion

Our localization design


White-line detection

Evolution and revolution


Devbot0 2005

Model 2006

Model 2007

Model 2008

Model 2009






?

How to design a system of systems?


• 5 agents: distributed system

• agents must be self-reliant

• minimise interaction/sync

• maximise cooperation

• aggressive environment

System of systems


• April 2011, German Open, Magdeburg

• July 2011, World Cup, Istanbul

• Dedicated goal keeper

• Robustified ball handling

• Passing during gameplay

Towards Istanbul, 2011

Documents

Design of Intelligent Robotics · RoboEarth •How to deal with a complex world? • Changing scenes • Many possible scenarios 12-03-2010 PAGE 11 •RoboEarth – learning and memorization