Robotic localization based on visual analysis. Global and local visual descriptors are extracted from images to offer an initial estimate of a robot's position as well as the necessary precision for localization. Compression of these descriptors allows for efficient transmission in distributed robotic systems. The localization process involves extracting compressed descriptors from images taken by a robot at different times and comparing them to determine its position.

1. Robotic Navigation
ROBOTIC LOCALIZATION BASED ON VISUAL ANALYSIS
Pedro Porto Buarque de Gusmão
UNINFO – Milan 06/10/2014

2. Robotic Navigation - Localization
Why?

3. The possibilities…
• Autonomous Driving – Precision in cm rather than m.
• Precise localization also for pedestrians.
• Intelligent Cleaning – Never miss a spot

4. Why MPEG CDVS?
Global Descriptors – Offers an a first, overall estimate of robot’s position.
Local Descriptors – Offers the necessary precision for localization.
Compression – Allows for efficient transmission in distributed systems.

5. Localization Process
Pavement @ t=n
Pavement @ t=n-τ
Robot
pt_grey_image
cdvs_extractor
Workstation
cdvs_compare(n,n-τ)CDVS Descriptors

6. Questions?
Thanks

7. This work is licensed under the
Creative Commons Attribution- NonCommercial-NoDerivs 3.0 Unported License.
To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/