- Tytuł:
- An ant-based filtering random-finite-set approach to simultaneous localization and mapping
- Autorzy:
-
Li, D.
Zhu, J.
Xu, B.
Lu, M.
Li, M. - Powiązania:
- https://bibliotekanauki.pl/articles/329854.pdf
- Data publikacji:
- 2018
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
simultaneous localization
simultaneous mapping
random finite set
probability hypothesis density
ant colony
lokalizacja jednoczesna
mapowanie jednoczesne
algorytm mrówkowy - Opis:
- Inspired by ant foraging, as well as modeling of the feature map and measurements as random finite sets, a novel formulation in an ant colony framework is proposed to jointly estimate the map and the vehicle trajectory so as to solve a feature-based simultaneous localization and mapping (SLAM) problem. This so-called ant-PHD-SLAM algorithm allows decomposing the recursion for the joint map-trajectory posterior density into a jointly propagated posterior density of the vehicle trajectory and the posterior density of the feature map conditioned on the vehicle trajectory. More specifically, an ant-PHD filter is proposed to jointly estimate the number of map features and their locations, namely, using the powerful search ability and collective cooperation of ants to complete the PHD-SLAM filter time prediction and data update process. Meanwhile, a novel fast moving ant estimator (F-MAE) is utilized to estimate the maneuvering vehicle trajectory. Evaluation and comparison using several numerical examples show a performance improvement over recently reported approaches. Moreover, the experimental results based on the robot operation system (ROS) platform validate the consistency with the results obtained from numerical simulations.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2018, 28, 3; 505-519
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł