Name
Title | ||
|---|---|---|
A robust set-valued state estimation approach to the problem of vision based SLAM for mobile robots |
Abstract | ||
|---|---|---|
The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using ideas and algorithms from robust control and estimation theory. Using a stereo-vision based sensor, a nonlinear measurement model is derived which leads to nonlinear measurements of the landmark coordinates along with optical flow based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear domain and solved using a robust linear filter. The linear filter is guaranteed stable and the SLAM state estimation error is bounded within an ellipsoidal set. No similar results are available for the commonly employed extended Kalman filter which is known to exhibit divergence and inconsistency characteristics in practice. |
Year | Venue | Keywords |
|---|---|---|
2009 | Control Conference | kalman filters,slam (robots),image sequences,mobile robots,nonlinear filters,robot vision,robust control,set theory,state estimation,velocity measurement,slam state estimation error,analytical measurement transformation,divergence characteristics,ellipsoidal set,estimation theory,extended kalman filter,inconsistency characteristics,landmark coordinates,linear domain,nonlinear slam problem,nonlinear measurement model,optical flow based measurements,relative robot-landmark velocity,robust linear filter,robust set-valued state estimation approach,stereo-vision based sensor,vision based slam problem,visual simultaneous localization and mapping problem,robust filtering,stable slam,visual slam,mathematical model,simultaneous localization and mapping,robot kinematics,robustness,uncertainty |
Field | DocType | ISBN |
Extended Kalman filter,Nonlinear system,Linear filter,Control theory,Robustness (computer science),Estimation theory,Robust control,Simultaneous localization and mapping,Optical flow,Mathematics | Conference | 978-3-9524173-9-3 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pubudu N. Pathirana | 1 | 520 | 54.96 |
| Adrian n. Bishop | 2 | 334 | 25.08 |
| Andrey V. Savkin | 3 | 1431 | 178.60 |
| Samitha w. Ekanayake | 4 | 6 | 3.34 |
| Nicholas J. Bauer | 5 | 1 | 0.70 |