1. Haptic neural predictor in bilateral tele-operation systems Yuri Boiko Project Presentation for the course ELG 5121 Ottawa University yuri.boiko@rocketmail.com

2. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 2 - Principles of bilateral tele-operation - Smyth’s predictor for time delay compensation -Targeted scenarios: - moving elastic objects (example: beating heart surgery) - Haptic description of elastic moving object - Suggested design of haptic neural predictor - Model verification and testing - Conclusion Structure of presentation

3. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 3 Bilateral tele-operation set up

4. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 4 Schematic of bilateral tele-operation

5. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 5 Neural network based Smyth’s predictor

6. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 6 On-line neural network update

7. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 7 Model of moving elastic object X G Force sensor Elastic object Platform The elastic object on the moving platform for haptic experiment

8. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 8 Model: cutting the elastic object X Needle with force sensor Elastic object Platform Needle insertion into the elastic object in haptic experiment

9. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 9 http://www.youtube.com/watch?v=NI-UO6Ey7gs&feature=related The Chamberlain Group: Beating Heart Trainer Example of the periodically moving elastic object for haptic experiment

10. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 10 Remote robot training with neural network model NN 0 F X G x t1 g t1 x t1 x t2 x t3 Haptic force Input coordinates of force sensor Input coordinates of moving platform g t1 g t2 g t3 Neural network under training

11. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 11 NN 0 NN 1 X G X Trained neural model in the haptic Smith’s predictor x t1 g t1 x t1 x t2 x t3

12. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 12 NN 1 G g t1 Neural haptic predictor for elastic object position

13. Essay 1, ELG 5121 (26 September 2010) yuri.boiko@rocketmail.comSlide 13 Conclusions - new design of the Smyth predictor is suggested for bilateral tele-operation over moving elastic objects (such as beating heart in surgery); - neural predictor in this new design aims at synchronization of the master and remote robot movements with the movements of the elastic object (such as heart contractions); - extension of the model to the case of cutting the elastic object surface is considered.