Compressed Unscented Kalman Filter-Based SLAM
This paper proposes a real-time nonlinear filtering approach for the SLAM problem, termed as compressed Unscented Kalman filter (CUKF). A partial sampling strategy was recently proposed to make the computational complexity of the UKF quadratic with the state-vector dimension. However, the quadratic complexity remains intractable for the large-scale SLAM. To address this problem, we firstly prove the equivalence of the partial and full sampling strategies for the decoupled nonlinear system. Then...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the IEEE International Conference on Robotics and Biomimetics|
|01_Cheng_Compressed_Unscented_Kalman_2014.pdf||1.98 MB||Adobe PDF||Request a copy|
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