This document discusses cloud robotics, which involves robots outsourcing compute-intensive tasks like image and voice recognition to cloud infrastructure. Benefits include access to vast data and processing power, ability to instantly download new skills, and cheaper robot hardware. Examples presented are using cloud for object recognition and mapping. Challenges discussed are limited robot resources, dynamic networks, security, and issues around offloading computation and communication delays.

1. 한국해양과학기술진흥원
Cloud Robotics
2013.10.6
Sayed Chhattan Shah, PhD
Electronics and Telecommunications Research Institute, Korea
https://sites.google.com/site/chhattanshah/

2. 한국해양과학기술진흥원
2
Acknowledgements
Ken Goldberg, UC Berkeley, “Cloud Robotics”
Guoqiang Hu, NTU Singapore, “Cloud Robotics:
Architecture, Challenges and Applications”

3. 한국해양과학기술진흥원
Outline
 Introduction
 Applications
 Challenges
 Current Research
 Future Research Directions

4. 한국해양과학기술진흥원
Cloud Robotics
 Robots that rely on cloud-computing infrastructure to access
vast amounts of processing power and data
 Allow robots to offload compute-intensive tasks
 Image processing
 Voice recognition
 Robots can download new skills instantly
 Enabling Factors
 Mobile Devices
 Wireless networks
 Rapidly expanding Internet resources

5. 한국해양과학기술진흥원
Benefits
 Provides a shared knowledge database
 Organizes and unifies information about the world in a format
usable by robots
Offloads heavy computing tasks to the cloud
 Cheaper, lighter, easier-to-maintain hardware
 Longer battery life
 Less need for software pushes/updates
 CPU hardware upgrades are invisible & hassle-free
Skill / Behavior Database
 Reusable library of “skills” or behaviors that map to perceived task
requirements / complex situations

6. 한국해양과학기술진흥원
Example
 Cloud-enabled Object Recognition
 Google Goggles project

7. 한국해양과학기술진흥원
Example
 Robot Goggles
 Upload images -> Download Semantic
• Object name
• 3D model, mass, materials, friction properties
• Usage instructions - function, how to grasp, operate
• Context and Domain knowledge

8. 한국해양과학기술진흥원
Example
 Matrix Movie Scene
 For humans, still science fiction
 For robots?

9. 한국해양과학기술진흥원
Example
 Maps and Localization
 Shared and highly detailed maps of the world stored in the
cloud
 Updates can be published and immediately used

10. 한국해양과학기술진흥원
Cloud Robotics and Networked Robots

11. 한국해양과학기술진흥원
Cloud Robotics and Networked Robots

12. 한국해양과학기술진흥원
Cloud Robotics and Networked Robots
 Peer-based Model
 Proxy-based Model
 Clone-based Model

13. 한국해양과학기술진흥원
Cloud Robotics Projects
 Researchers at ASORO laboratory have built a cloud
computing infrastructure to generate 3-D models of
environments
 Allowing robots to perform simultaneous localization and
mapping much faster than by relying on their onboard
computers
• SLAM refers to a technique for a robot to build a map of the environment without
a priori knowledge, and to simultaneously localize itself in the unknown
environment
 The backend system consists of a Hadoop distributed file
system that can store data from laser scanners,
odometer data, or images and video streams from cameras

14. 한국해양과학기술진흥원
Cloud Robotics Projects
 At LAAS, Jean-Paul Laumond, and colleagues are creating object
databases for robots to simplify the planning of manipulation tasks
like opening a door
 The idea is to develop a software framework where objects come
with a "user manual" for the robot to manipulate them
 This manual would specify, for example, the position from which
the robot should manipulate the object
 The approach tries to break down the computational complexity of
manipulation tasks into simpler, decoupled parts:
 A simplified manipulation problem based on the object's "user
manual," and
 A whole-body motion generation by an inverse
kinematics solver, which the robot's computer can solve in real
time

15. 한국해양과학기술진흥원
Cloud Robotics Projects
 Gostai, a French robotics firm, has built a cloud robotics
infrastructure called GostaiNet, which allows a robot to perform
speech recognition, face detection, and other tasks remotely
 Gostai's Jazz telepresence robot uses the cloud for video recording
and voice synthesis

16. Cloud Robotics

17. 한국해양과학기술진흥원
Challenges
 Limited Resources
 Mobility
 Limited Power
 Dynamic Network Environment
 Security
 Computation Challenges
 Offload decision
 Offload strategy
 Communication Challenges
 Data transfer time

18. 한국해양과학기술진흥원
Cloud Robotics
 Same as:
 Remote computing?
 Mobile cloud computing?
 Mobile Grid Computing?