sdn and cloud robot - fiffif.kr/gfi-summit/12/mt/gfiw_mt_s_8_shinji shimojo.pdf · cloud robotics...

SDN and Cloud Robot Shinji ShimojoNICT/Osaka U

2012.09

Smart X = cyber infrastructure

SDN meets robot

from ON DEMAND to CYBERNETICS

In  house  sensor

Mobile  sensor heterogeneous  sensor  network

Wearable    device

Smart  X  =  Cyber  Physical  System

medical  sensor

• IoT (Internet of Things)

• billions of data sources, large scale data

• mobility, charn

• feature as a group or a set

• a new form of security and privacy

Cloud

Interior  Sensors

Mobile  Sensors Heterogeneous  Sensor  Network

Wearable  Device

Smart  X  =  Cyber  Physical  System＋SDN

Vital  Sensor

Multilayer  Overlay  Network  by  SDN

Customizable Overlay Network

e-healthNew Generation

ITSSmart grid Digital

Cynage

Cloud

Cloud

• share knowlege

• share infrastructure

• get service done

Cloud robotics• ROS

• PR2, Turtlebot

• Android

• Google

http://www.willowgarage.com/

cloud robotics by  James Kuffner, Google. at the IEEE International Conference on

Humanoid Robots, Dec. 2010

http://www.getrobo.com/getrobo_blog/2010/12/humanoids-2010-cloud-robotics.html

• Accumulated Knowledge

• User based Innovation

• Continuous evolution of infrastructure

• Open inovation

• Common Platform

Why Cloud robotics needs SDN

• Network Virtualization

• Software Defined Network

• ID/Locator Separation

• Contents Oriented Network

• In Network Processing

• Optical Networking

• Wireless Networking

New Generation Network Technology

A Swarm of Nano Quadrotors

Nathan Michael, Daniel Mellinger, Quentin Lindsey, and Vijay Kumar, ”The GRASP Multiple Micro UAV Testbed” Robotics & Automation Magazine, IEEE, pp. 56-65, Sept. 2010.

1KHz

100KHz

VICON

MATLAB

RC

ZigbeeDynamic Load balance between cycles

Adaptation for dramatic change of communication environment

Different type of security requirement

Communication requirement for Cloud Robotics

• flexible network service

• Dynamic change of configuration and resource allocation

• Network Virtualization

• Dramatic change of communication environment

• Cognitive wireless network、DTN

• Customized network service ntegrated with Cloud services

• SDN

• Layered Multiservice Network is a solution

Roscore

node nodenode node

scan: 33,55,scan: 33,55,

ROS framework

Roscore

node nodenode node

scan: 33,55,scan: 33,55,

Roscore

node nodenode node

scan: 33,55,scan: 33,55,

Pachube

Turtlebot in our Data center

stoker robot

Things we can do with cloud robot

• share knowledge among robots

• SLAM:Simultaneous Localization and Mapping

• AMCL:Adaptive Monte Carlo Localization

• share knowledge between robot and human

• Pachube: sensor information on the web

provide different network services in different network overlays

JGN-­‐X  technology  layers

Network A(L1/L2)

Network B(L2/L3)

Network C(L2)

Virtual Network Integration by PseudoWire

OpenFlow

VPLS

Physical Networks

SDTN

IPv6 network

IPv4/6 translation by SA46T

IPv4 networkLayer2  with  QOS

Network D(L2/L3)

DCN  s3ching

RISE

Vnode DPN

Mul3layerMeasuments

#3#2#1

Aggregate

19

Ongoing  research  project:DTN  for  cloud  robots

Data Aggregation & Analysis

＋

Commands

Sensor Data

Commands

Sensor DataSensor Data

Analyze Sensor Data

Aggregation of Sensor data

Wireless AP Area

Robot

(An example of Cloud Robot)

Sensor Data

DTN  func3on  on  the  network  nodes

DTN  between  Robots  and  

Cloud

DTN  between  Robots

20

From  ON  DEMAND  to  CYBERNETICS

Data Aggregation & Analysis

＋

Commands

Sensor Data

Commands

Sensor DataSensor Data

Analyze Sensor Data

Aggregation of Sensor data

Wireless AP Area

Robot

(An example of Cloud Robot)

Sensor Data

DTN  func3on  on  the  network  nodes

Multilayer  Overlay  Network  by  SDN

Customizable Overlay Network

Ongoing  research  project:Platform  for  the  real-‐‑‒world  analysis

CrimeStatus

NaturalDisasters

AccidentStatus

EconomicStatus

CrimePreven3on

SmartLogis3cs Observa3ons

Health  cares

EnvironmentalMonitoring

DisasterManagements

Marke3ng

Analyze Sensor DataAnalyze Contents

SocialPhenomenon

New-­‐genera3on  ICT  Services

TrafficStatus

InternetCollect Sensor Data

Collect Contents

Combine various kind of information sources

Analyze status / phenomenon in the real-world

The  aim  of   the  project  is   to  provide  a  plaJorm  for   real-­‐world  analysis  using  various  data  sources  such  as  sensors,  contents  of  the  social  network  services,  etc.

21

Global Testbed is the field

Thank you감사합니다

Presented version is here!https://sites.google.com/site/sshimojo/talks

Acknolegement

• Yuichi Teranishi

• Manabu Higashida

• Kotaro Takaura

• Naoko Toyokawa

• Eiji Kawai