NAO Robot Music Application for Children Fabrianne Effendi EEE30 - - PowerPoint PPT Presentation

nao robot music application
SMART_READER_LITE
LIVE PREVIEW

NAO Robot Music Application for Children Fabrianne Effendi EEE30 - - PowerPoint PPT Presentation

Development of Interactive NAO Robot Music Application for Children Fabrianne Effendi EEE30 Why NAO? Interactive and engaging, thus children learn better from NAO Caters to needs of various children Autism kids more receptive to


slide-1
SLIDE 1

Development of Interactive NAO Robot Music Application for Children

Fabrianne Effendi EEE30

slide-2
SLIDE 2

Why NAO?

◎ Interactive and engaging, thus children learn better from NAO ◎ Caters to needs of various children ◉ Autism kids more receptive to NAO than humans ◎ Immense potential in the field of music education

slide-3
SLIDE 3

Methodology

slide-4
SLIDE 4

Overview of music application

slide-5
SLIDE 5

3-step process to impart new music skills

slide-6
SLIDE 6

Key interactivity features

slide-7
SLIDE 7

Speech Recognition Feature

Allows NAO to recognise predefined words or phrases, subsequently responding to it.

slide-8
SLIDE 8

Animated Say Box

Used to increase interactivity and make the robot more human-like through carrying out human-like gestures while it speaks

slide-9
SLIDE 9

Python Script Box

Allows for more complex and precise behaviours to be programmed

slide-10
SLIDE 10

Timeline Box

Contains a motion layer and multiple behaviour layers, allowing NAO to do multiple things simultaneously

slide-11
SLIDE 11
slide-12
SLIDE 12

Flashcards

Help children in their learning as they are visually appealing, capturing children’s attention

slide-13
SLIDE 13

Results & Discussion

slide-14
SLIDE 14

Finding Optimal Speech Recognition Confidence Threshold

Environment Accurate detection Confidence level Quiet ✓ 25-45% Noisy ✗ <25% Thus, NAO’s optimal speech recognition confidence threshold was set to 25% for optimal detection accuracy. Confidence level for speech recognition

slide-15
SLIDE 15

Evaluation

  • f

methods to integrate flashcards with NAO robot music application

slide-16
SLIDE 16

Object recognition

Mode of detection Able to differentiate flashcards Accurate detection under various lighting conditions Speed of detection (1: slowest; 3: fastest) Main disadvantage Detects images based

  • n

the recognition

  • f

key points ✗ (only able to differentiate 3D

  • bjects)

✓ 1 Unable to detect external shape

  • f

2D objects

slide-17
SLIDE 17

ALColourBlob Detection

Mode of detection Able to differentiate flashcards Accurate detection under various lighting conditions Speed of detection (1: slowest; 3: fastest) Main disadvantage Detects 2 dimensional vision-based colour blob. ✓ ✗ (since it is dependent on predefined RGB colour) 2 May detect similar colour from surroundings before flashcard is shown, resulting in incorrect detection

  • f

flashcard

slide-18
SLIDE 18

NAOmark

Mode of detection Able to differentiate flashcards Accurate detection under various lighting conditions Speed of detection (1: slowest; 3: fastest) Detects unique NAOmark. ✓ ✓ 3 Each unique NAOmark corresponds to a unique integer output

slide-19
SLIDE 19

NAO Video

slide-20
SLIDE 20

Conclusion

slide-21
SLIDE 21

Conclusion

◎ Successfully developed NAO robot music application ◎ Demonstrates future potential for humanoid robots to be used as an educational learning tool in classrooms ◎ Future work: ◎ To test the application

  • n

children ◎ To customise music application for children with autism

slide-22
SLIDE 22

Thank you!