SLAM with SC-PHD filters: an underwater vehicle application

​
​ ​ ​ ​
Lee, Chee Sing
​ ​ ​ ​
Nagappa, Sharad
orcId Palomeras Rovira, Narcís​ researcherId Palomeras Rovira, Narcís​ scopusId Palomeras Rovira, Narcís​ ​
Palomeras Rovira, Narcís
​ ​ ​ ​
Clark, Daniel E.
orcId Salvi, Joaquim​ ​ scopusId Salvi, Joaquim​ ​
Salvi, Joaquim
Full Text
SLAM-C-PHD.pdf embargoed access ​
Request a copy
Request a copy
When filling the form you are requesting a copy of the article, that is deposited in the institutional repository (DUGiDocs), at the autor or main autor of the article. It will be the same author who decides to give a copy of the document to the person who requests it, if it considers it appropriate. In any case, the UdG Library doesn’t take part in this process because it is not authorized to provide restricted articles.
​
Share
​
The random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework within the sensor fusion community for developing multiple-target tracking algorithms. These techniques are also gaining traction in the field of feature-based simultaneous localization and mapping (SLAM) for mobile robotics. Here, we present one such instance of this approach with an underwater vehicle using a hierarchical multiobject estimation method for estimating both landmarks and vehicle position ​
​Tots els drets reservats
Show full item record