Difference between revisions of "Self calibration of multiple odometric sensors"

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(Created page with "{{ProjectProposal |title=Self calibration of multiple odometric sensors mounted on the same platform |image=HandEye.jpg |description=An odometric sensor measures the path foll...")
 
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'''Expected outcome:'''
 
'''Expected outcome:'''
software for the self calibration of a set of odometry systems mounted on the same robot
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*software for the self calibration of a set of odometry systems mounted on the same robot
  
 
'''Required skills or skills to be acquired:'''
 
'''Required skills or skills to be acquired:'''

Revision as of 16:15, 16 April 2012

Title: Self calibration of multiple odometric sensors mounted on the same platform
HandEye.jpg

Image:HandEye.jpg

Description: An odometric sensor measures the path followed by a robot in an incremental way (e.g., wheel mounted encoders, visual odometry, scan matching based odometry, etc.) . Having several odometry sensors mounted on the same platform can significantly improve the accuracy and robustness of the overall system but requires proper calibration of relative positioning and possible biases. We are interested in the development of techniques for the self calibration of a multi sensor based odometry sensor. These techniques could be inspired by classical non-linear optimization techniques used in the hand and eye problem but they could use techniques from Simultaneous Localization and Mapping. According to the setup, some information on the real position of the system may exists (i.e., external tracking system or GPS); the approach should be able to use this information as well.

Material:

  • datasets with real data
  • a few odometric system implementations
  • C++ libraries for non linear optimization

Expected outcome:

  • software for the self calibration of a set of odometry systems mounted on the same robot

Required skills or skills to be acquired:

  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 2012/04/01
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: none
Level: Ms
Type: Thesis
Status: Active