Nao in the cloud

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Many teams in the world are working on the topic Cloud Robotics. This talk introduce you how to connect the Nao robot with the cloud to share knowledge about objects, plans and environments with other robots. With this approach it is possible, that heterogeneous robots can exchange executable robot apps among eachother. The RoboEarth webservice will be used to store robotic-specific information. Robots are able to share knowledge via RoboEarth. So Robots are not longer on their own - they can benefit from the experience other robots.

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Nao in the cloud

  1. 1. 04.06.2013 NAO TECH DAY @ ALDEBARAN ROBOTICS NAO IN THE CLOUD FLORIAN JOHANNßEN florixcan.johannssen@haw-hamburg.de 1
  2. 2. Outline  Motivation  Cloud Robotics  Related Work  Current Research  Conclusion Motivation Cloud Robotics Related Work Current Research Conclusion 2
  3. 3. Motivation  Humans learn from each other via the Internet  Robots are limited by  Costs  Hardware resources  Local knowledge  Why don‘t robots use the Internet as well?  Robots are WIFI-enabled  Robots have high-level interfaces 3 Motivation Cloud Robotics Related Work Current Research Conclusion
  4. 4.  Cloud Robotics = Cloud Computing + Robotics  Knowledge sharing  Object descriptions  Plans  Environments  Outsourcing  Speech & object recognition  Reasoning Cloud Robotics 4 Motivation Cloud Robotics Related Work Current Research Conclusion
  5. 5. Origin of cloud-enabled robots 5 The idea was originated by the University of Tokyo  Remote-brained robots by Masayuki Inaba (1993) [1]  Mechanical animals using the remote-brained approach (1994) [2]  A remote-brained full-body humanoid… (1997) [3]  A Platform for Robotics Research Based on the Remote- Brained Robot Approach (2000) [4] Motivation Cloud Robotics Related Work Current Research Conclusion
  6. 6. Advantages and Opportunities 6  Improvement of the learning mechanism  Robots benefit from the experiences of others  Robots are able to share executable plans  Handling of tasks in unknown environments  Robots are able to perform more generic challenges  Offload compute-intensive tasks  Massively-parallel computation on demand  Building of lighter, cheaper and smarter robots Motivation Cloud Robotics Related Work Current Research Conclusion
  7. 7. Knowledge sharing for robots 7  RoboEarth Knowledge Database by [5]  Eindhoven University of Technology  Philips Innovation Services  University of Stuttgart  Swiss Federal Institute of Technology Zurich  University of Zaragoza  Technical University Munich  RobotShare by [6]  University of Utah Motivation Cloud Robotics Related Work Current Research Conclusion
  8. 8. Outsourcing heavy tasks  Rapyuta: The RoboEarth cloud engine by [7]  The RoboEarth team  DaVinCi by [8]  Agency for Science, Technology and Research Singapore  Cloud-Based robot grasping with the Google object recognition engine by Google [9]  Smartphone Robot Romo by Romotive [10] 8 Motivation Cloud Robotics Related Work Current Research Conclusion 99 $
  9. 9. Current Research 9  Sharing executable plans among several Nao robots [12] [11] Motivation Cloud Robotics Related Work Current Research Conclusion
  10. 10. 10 [13] RoboEarth Motivation Cloud Robotics Related Work Current Research Conclusion
  11. 11. Architecture 11 Ubuntu ROS KnowRob CRAM-Core RoboEarth Nao Wrapper Motivation Cloud Robotics Related Work Current Research Conclusion
  12. 12. Abstract Plan 12 [14] Motivation Cloud Robotics Related Work Current Research Conclusion
  13. 13. KnowRob - Request 13 re_download_action_recipe(‘serve a drink’, robot: ‘MyRobot’, Recipe), re_generate_cpl_plan(Recipe, CplPlan). ( d e f - t o p - l e v e l - p l a n s e r v e - a - d r i n k ( ) ( wi t h - d e s i g n a t o r s ( ( b o t t l e 1 ( o b j e c t ‘ ( ( name b o t t l e 1 ) ( type d r i n k i n g - b o t t l e ) ) ) ) ( bed1 ( o b j e c t ‘ ( ( name bed1 ) ( type b e d p i e c e - o f - f u r n i t u r e ) ) ) ) ... [15] Motivation Cloud Robotics Related Work Current Research Conclusion
  14. 14. Architecture 14 [13] [12] Ubuntu ROS KnowRob CRAM -Core RoboEarth Nao Wapper Motivation Cloud Robotics Related Work Current Research Conclusion
  15. 15.  Development of an interface between Nao and RoboEarth via the ROS-middleware Interface 15 [16] [13] [15] (def-top-level-plan grasp-bottle () (with-designators ((fridge (object '((type fridge)))) (bottle-loc (location `((inside ,fridge)))) (bottle (object `((type bottle) (at ,bottle-loc))))) (setf fridge (perceive-object fridge)) (achieve `(object-in-hand ,bottle :right)))) ... Motivation Cloud Robotics Related Work Current Research Conclusion
  16. 16. Scenario 16  Solving a task which the Nao hasn´t performed before  Scanning the RoboEarth Database for the task  Translating an abstract plan to a CRAM plan  Nao downloads the executable plan via KnowRob  Solving the task Motivation Cloud Robotics Related Work Current Research Conclusion
  17. 17. Technical challenges 17  How to connect Nao with the cloud?  Is it possible that heterogeneous robots are able to share executable plans?  Different capabilities  Which kind of abstraction layer?  Latency problems  Without their wireless connection to the cloud, robots become brainless  Security problems  Would you store information about your patients in a cloud for robots ?  What happens if the cloud is hacked? Motivation Cloud Robotics Related Work Current Research Conclusion
  18. 18. Conclusion 18  Cloud Robotics = Cloud Computing + Robotics  Knowledge sharing among heterogeneous robots  Offloading heavy tasks  Many projects are working on this topic  Opportunities  Improvement of the learning mechanism  Robots are able to share executable plans  Massively-parallel computation on demand  Nao in the Cloud  Middleware ROS  CRAM Plan Language  KnowRob Motivation Cloud Robotics Related Work Current Research Conclusion
  19. 19. References 1. Inaba, Masayuki. Remote Brained Robots. Tokio, 1993 2. Inaba M., Kagami, S., Ishikawa, T., Kanehiro, F., Takeda, K., Inoue, H., Vision-based adaptive and interactive behaviors in mechanical animals using the remote-brained approach. Tokyo, 1994 3. Inaba M., Ninomiya, T., Hoshino, Y., Nagasaka, K., Kagami, S., Inoue, H. A remote-brained full-body humanoid with multisensor imaging system of binocular viewer, ears, wrist force and tactile sensor suit, 1997 4. Inaba M., Kagami S., Kanehiro F., Hoshino Y., Inoue H. A Platform for Robotics Research Based on the Remote-Brained Robot Approach 5. Zweigle, Molengraft, Andrea, Häussermann. RoboEarth – connecting Robots worldwide.Eindhoven, 2009 6. Fan, Xiuyi, und Thomas C. Henderson. RobotShare: A Google for Robots. 2007 7. D. Hunziker, M. Gajamohan, M. Waibel, and R. D’Andrea. Rapyuta: The RoboEarth Cloud Engine. 2013 8. Enti, V.R.; Liu Bingbing; Wu Xiaojun; Baskaran, K.; Foong Foo Kong;Kumar, A.S.; Kang Dee Meng; Goh Wai Kit. DAvinCi: A cloud computing framework for service robots. 2010 9. Ben Kehoe, Akihiro Matsukawa, Sal Candido, James Kuffner, and Ken Goldberg.. Cloud-Based Robot Grasping with the Google Object Recognition Engine. 2013 10. http://romotive.com/images/romo-frontal.png 11. http://www.roboearth.org/ 12. http://asep-championship.com/wp-content/uploads/2011/11/NAO-4_cutout.png 13. D. Marco, M. Tenorth, K. Häussermann, O. Zweigle, P. Levi. RoboEarth Action Recipe Execution. 2011 14. M. Tenorth, A. Perzylo, R. Lafrenz and M. Beetz. The RoboEarth language: Representing and Exchanging Knowledge about Actions, Objects, and Environments, 2012 15. M. Beetz, L. Mösenlechner, M. Tenort. CRAM -- A Cognitive Robot Abstract Machine for Everyday Manipulation in Human Environments 16. http://ros.org/doc/groovy/api/nao_driver/html/classnao__driver_1_1nao__driver__naoqi_1_1NaoNode.html 19
  20. 20. THANK YOU FOR YOUR ATTENTION I´LL BE HAPPY TO ANSWER ANY QUESTIONS!

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