2D Cloud Template Matching - A comparison between Iterative Closest Point and Perfect Match

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Sobreira, H (Author) Other; Rocha, LF (Author) FEUP; Costa, C (Author) Other; Lima, J (Author) Other; Paulo Gomes da Costa (Author) FEUP; António Paulo Moreira (Author) FEUP

Conference proceedings International

Title: 2016 International Conference on Autonomous Robot Systems and Competitions, ICARSC 2016, Bragança, Portugal, May 4-6, 2016

Pages: 53-59

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00M-9EC

DOI: 10.1109/icarsc.2016.13

Abstract (EN): Self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to algorithms accuracy, robustness and computational efficiency. In this paper we present the comparison of two of the most used map-matching algorithm, which are the Iterative Closest Point and the Perfect Match. This category of algorithms are normally applied in localization based on natural landmarks. They were compared using an extensive collection of metrics, such as accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to outliers in the robots sensors data. The test results were performed in both simulated and real world environments.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7