Autor:

Nowak, Tomasz ; Nowicki, Michał ; Skrzypczyński, Piotr

Współtwórca:

Yao, Baozhen - ed. ; Wang, Shuaian - ed. ; Asian, Sobhan - ed.

Tytuł:

Vision-based positioning of electric buses for assisted docking to charging stations

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, volume 32 (2022)

Temat i słowa kluczowe:

AI transport ; localization ; monocular vision ; deep learning ; keypoints ; advanced driver assistance system

Abstract:

We present a novel approach to vision-based localization of electric city buses for assisted docking to a charging station. The method assumes that the charging station is a known object, and employs a monocular camera system for positioning upon carefully selected point features detected on the charging station. While the pose is estimated using a geometric method and taking advantage of the known structure of the feature points, the detection of keypoints themselves and the initial recognition of the charging station are accomplished using neural network models. ; We propose two novel neural network architectures for the estimation of keypoints. Extensive experiments presented in the paper made it possible to select the MRHKN architecture as the one that outperforms state-of-the-art keypoint detectors in the task considered, and offers the best performance with respect to the estimated translation and rotation of the bus with a low-cost hardware setup and minimal passive markers on the charging station.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2022

Typ zasobu:

artykuł

DOI:

10.34768/amcs-2022-0041

Strony:

583-599

Źródło:

AMCS, volume 32, number 4 (2022) ; click here to follow the link

Jezyk:

eng

Licencja CC BY 4.0:

click here to follow the link

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego