Abstract
Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.
Highlights
The determination of the position of a moving object is an essential part of many complex applications
While outdoor localization can be achieved with the help of global satellite networks including the Global Positioning System (GPS) and the Global Navigation Satellite System (GLONASS), an efficient indoor localization is still an open problem [1,2]
This section provides the background of the presented work. It outlines the simulation-based design strategy it adopts, relevant scan matching methods such as the iterative closest point algorithm, the fundamentals of the cross-correlation principle and the optimization process implemented by the differential evolution
Summary
The determination of the position of a moving object is an essential part of many complex applications. While outdoor localization can be achieved with the help of global satellite networks including the Global Positioning System (GPS) and the Global Navigation Satellite System (GLONASS), an efficient indoor localization is still an open problem [1,2]. It can be defined as the process of obtaining the location of a moving object in an indoor environment [2]. It outlines the simulation-based design strategy it adopts, relevant scan matching methods such as the iterative closest point algorithm, the fundamentals of the cross-correlation principle and the optimization process implemented by the differential evolution
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
