Thank you very much for the explanation! This intricacy of sensor models was something I used to overlooked and would consider the gaussian model alone.
Why do the sensor measurements have conditional independence (on the state), and not a general independence? In case of a lidar, each measurement is independent of the other irrespective of the state right?
Thank you, great lecture. Is it a part of an old series of lecture? Or just started an new series. As now a new semester is going to start. If possible can you just briefly describe a road map for this series. Most of you reading recommendations are from Probabilistic Robotics, can you please suggest more reading materials from other sources on SLAM, Sensor Fusion, Kalman Filtering and Particle Filters for Robot localization. Your lectures are of great help for researchers in the field of robotics.
@@CyrillStachniss Hi professor Stanchiss, do you have any recommendations for related hands-on project/exercises to enhance our understanding on these great concepts ?? thanks a lot
