1. Visual Tracking on an Autonomous Self-contained Humanoid Robot
Mauro Rodrigues, Filipe Silva, Vítor Santos
University of Aveiro
CLAWAR 2008
Eleventh International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines
08 – 10 September 2008, Coimbra, Portugal

2. Outline Overview Objectives Self-Contained Platform Vision System
Experimental Results
Conclusions
08-10 September 2008

3. Overview Humanoid Platform
Humanoid Robot developed at University of Aveiro
Ambition is participation at Robocup
Platform composed of 22 DOF’s
Head on a PTU arrangement
Up to 70 cm height and a mass of 6,5 kg
08-10 September 2008

4. Overview Distributed Control Architecture
Master/Multi-Slave configuration on CAN Bus
Central Processing Unit:
Image processing and visual tracking
External computer interaction for monitorization, debug or tele-operation
Master
CPU/Slaves communication interface
Slaves
Interface with actuators and sensors
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5. Objectives Central Processing Unit Integration
Computational autonomy
Development environment
Vision System Development
Visual Tracking Approach
Detection and tracking of a moving target (ball)
08-10 September 2008

6. Self-Contained Platform
CPU standard PCI-104
AMD Geode 500MHz
512Mb RAM
SSD 1Gb
Video Signal Capture
PCMCIA FireWire board
Dual PCMCIA PC104 module
UniBrain 30fps (640x480) Camera
Development Environment
Linux based
OpenCV
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7. Vision System
08-10 September 2008

8. Segmentation - H, S and V Components
Vision System
Acquisition
Segmentation - H, S and V Components
Object Location
Pre-processing
Mask
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9. Vision System Dynamic Region of Interest (ROI) Reduced noise impact
Faster calculus
No ROI
With ROI
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10. Vision System Dynamic Region of Interest (ROI)
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11. Vision System Visual Tracking Approach
Keep target close to image centre
Image based algorithm
Fixed gains proportional law,
, joint increment vector
, constant gain matrix
, error vector defined by the ball’s offset
Variable gains nonlinear law,
08-10 September 2008

12. Experimental Results Self-Contained Platform
Acquisition
libdc1394 based library
320x240 with down-sampling: ~24ms
Processing
Without dynamic ROI: 15ms
With dynamic ROI: 11ms
Total = ~40ms
25Hz
Times (ms)
Max. (ms)
Min. (ms)
Avg. (ms)
St. Dev.
acquisition
32,4020
11,8780
13,6820
2,0275
pyr down
25,9050
9,4730
9,8432
1,6330
segmentation
41,6030
9,3320
9,8456
2,4185
centroid location
3,2550
0,3970
1,3079
0,4478
control
0,1590
0,0140
0,0154
0,0093
actuation
37,2460
2,1670
4,4850
2,6913
total
118,6600
35,9060
39,1520
7,1468
08-10 September 2008

13. Experimental Results Visual Tracking
Ball alignment
~1s
Stationary error (~7 pixels)
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14. Experimental Results Visual Tracking
Pan tracking with fixed gains
Error increases in frontal area of the robot
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15. Experimental Results Visual Tracking
Fixed Gains
Variable Gains
Pan tracking with variable gains
Frontal area error reduced
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16. Experimental Results Visual Tracking
Tilt tracking with variable gains
Error similar to the pan tracking
Trunk increases the error
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17. Experimental Results Visual Tracking
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18. Conclusions
Implemented architecture separates the high-level vision processing from the low-level actuators control
Dynamic Region of Interest guarantees a greater noise immunity and faster calculus
Low error location and alignment with stationary target, fast convergence
Tracking error reveals the need of a more sophisticated control
Autonomous Self-Contained Humanoid Platform
25Hz average processing rate, sufficient to deal with fast-stimuli and other quick changing visual entries
08-10 September 2008

19. Future Work Validate ball detection through shape detection
Recognition of other elements, such as the ones present at the Robocup competition
Explore alternative techniques of Visual Servoing
Study the influence of the robot’s movement on the visual information and on the tracking system’s performance
08-10 September 2008

20. Thank you for your atention
08-10 September 2008