Autor:

Li, Demeng ; Zhu, Jihong ; Xu, Benlian ; Lu, Mingli ; Li, Mingyue

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Tytuł:

An ant-based filtering random-finite-set approach to simultaneous localization and mapping

Temat i słowa kluczowe:

simultaneous localization and mapping (SLAM) ; random finite sets ; probability hypothesis density ; ant colony

Abstract:

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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2018

Typ zasobu:

artykuł

DOI:

10.2478/amcs-2018-0039

Strony:

505-519

Źródło:

AMCS, volume 28, number 3 (2018) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego