Difference between revisions of "Indoor localization system based on a gyro and visual passive markers"
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===The Project in short=== | ===The Project in short=== | ||
− | #. Predict new robot pose | + | Using SLAM technique we want to develop an indoor system based on a gyroscope, an accelerometer and a camera. |
+ | |||
+ | |||
+ | ===SLAM Algorithm we use=== | ||
+ | #. Predict new robot pose with Gyroscope | ||
#. Modify the covariance | #. Modify the covariance | ||
#. For each of the M observed landmarks i: | #. For each of the M observed landmarks i: |
Revision as of 09:58, 4 June 2010
Indoor localization system based on a gyro and visual passive markers
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Short Description: | This project aims at developing autonomous moving systems based on a gyro and passive markers |
Coordinator: | |
Tutor: | MatteoMatteucci (matteo.matteucci@polimi.it), SimoneCeriani (ceriani@elet.polimi.it), DavideMigliore (d.migliore@evidence.eu.com) |
Collaborator: | |
Students: | DarioCecchetto (dario.cecchetto@mail.polimi.it), LorenzoConsolaro () |
Research Topic: | |
Start: | 2009/06/01 |
End: | 2010/04/25 |
Status: | Active |
Level: | Bs |
Type: | Thesis |
What we use
- Eclipse for C/C++
- An STR9 Cam based module from ST
- A STM32 Gyroscope based module from ST
The Project in short
Using SLAM technique we want to develop an indoor system based on a gyroscope, an accelerometer and a camera.
SLAM Algorithm we use
- . Predict new robot pose with Gyroscope
- . Modify the covariance
- . For each of the M observed landmarks i:
- . Compute hi and its Jacobian.
- . For each dimension j of the observation hi:
- Compute the scalar Sij
- Computation of Kij.
- Update the filter state vector
- Update the filter covariance Pk | k
- . If necessary, introduce new landmarks in the map.