1. Design of an Intelligent Visual Acoustic Humanoid Robot Ming-Yuan Shieh, Ming-Hung Tsai, Yen-Shao Chen Southern Taiwan University, Taiwan

2. 2 Outline  Abstract  Introduction  Visual System  Acoustic System  Locomotion Control System  Simulation Results  Experimental Results  Conclusions

3. 3 Abstract  Intelligent Visual Acoustic humanoid Robot (IVAR) consist of  Visual recognition subsystem  Speech recognition subsystem  Locomotion controller subsystem  The robot is mainly based on its visual system but assisted by its acoustic and postural control systems.

4. 4 Introduction  Observers like Bill Gates believe that by 2025 we could have robots in every home.  In famous movie “A.I.”  the protagonist is a humanoid robot with full of passions who often pours his feelings to a considerate mechanical bear.  Because of this, many approaches or projects aim to design a robot to accompany and pleasure the children.

5. 5 Visual System  The diagram of color recognition show  It consists of image filter, color space transform,color pattern matching. Lowpass filter RGB → YCbCr Fit→Original color Not→black color

6. 6 Color Space Transform  We transform image into the YCbCr color space formula  By using YCbCr model, one can easily distinguish intensity information of the image from it color data.  A jump searching algorithm is adopted to reduce the computing loads.

7. 7 Acoustic System  In the figure, it display the proposed configuration of the acoustic system  In this disposal, there are four microphones mounted as a mask at each side.  Since the quadratic disposal could receive all the sounds come from any direction.  it provides omnibearing detection method to determine the exact direction of the signal.

8. 8 Locomotion Control System  We adopt an ANFIS based identifier to determine the dynamic model between the inputs and the outputs of the locomotion control system.

9. 9 Integrated ANFIS Controller  These detected data can provide as the inputs of the integrated proposed ANFIS controller to determine adaptive control actions.  The ANFIS controller consists of 10 sub-controllers  it needs to be training for better system performance

10. 10 ANFIS Structure  It is a seven-input and single-output neuro-fuzzy network.  The error signals of outputs can be propagated back and used to adjust the parameters of the controller.

11. 11 Simulation Results

12. 12 Image Recognition  One can search the color of the ball within 140<Cb<160 and 100<Cr<120 from this image.

13. 13 The Hardware

14. 14 Experiment Result 1.Robot Walking

15. 15 Experiment Result 2.Visual Recognition on Objective

16. 16 Conclusions  This paper presents a scheme based on a visual and acoustic servo system.  The design procedures include  distinguishing the color of objects  to perform system identification of the biped robot by an ANFIS  The successful results of simulations and experiments demonstrate the feasibility of the proposed schemes.

17. 17 Thanks for your attendance!