MOOC - Sensor Fusion Expert
Sensor Fusion In-Depth
The last unit of this job role makes a profound and detailed description of sensor fusion and provides insights on important notions and procedures when performing sensor fusion techniques.
Feature-Based SLAM (Simultaneous Localization and Mapping) Methods and its EKF (Extended Kalman Filter) Solution:
This learning element provides students with a comprehensive description and understanding of the Simultaneous Localization and Mapping (SLAM) problem. In addition, this element presents the Extended Kalman Filter (EKF) as a solution to the problem explaining each step of its operation. Finally, this element briefly explains other SLAM algorithms, UKF SLAM, Fast SLAM, etc.
SFE.U4.E6.PC1
The student is able to define and understand SLAM.
SFE.U4.E6.PC2
The student recognizes and critically understands the challenges behind the SLAM problem.
SFE.U4.E6.PC3
The student is able to acknowledge the EKF solution and understand each step of its operation.
SFE.U4.E6.PC4
The student can examine and analyse concrete examples of the application of the EKF to solve the SLAM problem.
SFE.U4.E6.PC5
The student is able to setup an EKF for SLAM.
SFE.U4.E6.PC6
The student recognizes the existence of other SLAM algorithms (UKF SLAM, Fast SLAM, ...) and briefly defines and distinguishes their approaches.