Global Localization of Unmanned Ground Vehicles Using Swarm Intelligence and Evolutionary Algorithms

Carvalho, João L. C.; Farias, Paulo Cesar Machado de Abreu; Filho, Eduardo Furtado Simas

doi:10.1007/s10846-023-01813-6

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article4

Other1

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 5 publications

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Explainable machine learning models for defects detection in industrial processes

Oliveira,

Sant’Anna,

da Silva

2024

Computers & Industrial Engineering

View full text Add to dashboard Cite

Explainable machine learning models for defects detection in industrial processes

Oliveira,

Sant’Anna,

da Silva

2024

Computers & Industrial Engineering

View full text Add to dashboard Cite

2D-Localization Based on Tracking Antenna Using Artificial Intelligence Mapping (AIM) Approach

Madany

2023

IEEE Access

View full text Add to dashboard Cite

Many recent low-range applications require only two-dimensional localization. It is more dependable and simpler to use in real-time low-power and range applications because it requires significantly fewer calculations than three dimensions. As antennas can function as sensors in this system, they are regarded as crucial components in the development of localization systems. To avoid a relatively difficult object detection and achieve 360° azimuth plane coverage, the antenna must be as small as possible. The purpose of this study is to design an effective algorithm for the 2D-localization of low-range object positioning using the proposed Artificial Intelligence Mapping (AIM) approach. The proposed AIM approach's modelling and simulation of object localization based on a tracking antenna and the proposed Modified Triangulation Method (MTM) are introduced and analyzed. The design and implementation of the object-localization system were completed. To fulfil the specific aim and suggested AIM approach, the practical 2D-Localization Object System (2D-LOS) uses a commercial identification system. Several trace scenarios for the tracking antenna were illustrated, tested, and compared with samples from other methods in the literature to demonstrate the effectiveness of the proposed localization method for different low-range applications. The proposed AIM approach, which is based on real-world data, has a relatively low resolution and a small error difference.

show abstract

Sideslip Angle Estimation of Uncertain Vehicle System Based on Robust Extended Kalman Filter

He,

Yin,

Ren

et al. 2023

2023 IEEE International Automated Vehicle Validation Conference (IAVVC)

View full text Add to dashboard Cite

Global Localization of Unmanned Ground Vehicles Using Swarm Intelligence and Evolutionary Algorithms

Cited by 5 publications

References 51 publications

Explainable machine learning models for defects detection in industrial processes

Explainable machine learning models for defects detection in industrial processes

2D-Localization Based on Tracking Antenna Using Artificial Intelligence Mapping (AIM) Approach

Sideslip Angle Estimation of Uncertain Vehicle System Based on Robust Extended Kalman Filter

Contact Info

Product

Resources

About