An FPGA implementation of the SMG-SLAM algorithm

Authors:
Grigorios Mingas;Emmanouil Tsardoulias;Loukas Petrou
Affiliations:
Aristotle University of Thessaloniki, Faculty of Engineering, Department of Electrical and Computer Engineering, Division of Electronics and Computer Engineering, 54006 Thessaloniki, Greece;Aristotle University of Thessaloniki, Faculty of Engineering, Department of Electrical and Computer Engineering, Division of Electronics and Computer Engineering, 54006 Thessaloniki, Greece;Aristotle University of Thessaloniki, Faculty of Engineering, Department of Electrical and Computer Engineering, Division of Electronics and Computer Engineering, 54006 Thessaloniki, Greece
Venue:
Microprocessors & Microsystems
Year:
2012

Citing 9
Cited 1

Iterative point matching for registration of free-form curves and surfaces

International Journal of Computer Vision
FastSLAM: a factored solution to the simultaneous localization and mapping problem

Eighteenth national conference on Artificial intelligence
Genetic Algorithms Using Parallelism and FPGAs: The TSP as Case Study

ICPPW '05 Proceedings of the 2005 International Conference on Parallel Processing Workshops
Proposal of flexible implementation of genetic algorithms on FPGAs

Systems and Computers in Japan
An efficient problem-independent hardware implementation of genetic algorithms

Neurocomputing
A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots

Journal of Signal Processing Systems
A Reconfigurable Architecture for Stereo-Assisted Detection of Point-Features for Robot Mapping

RECONFIG '09 Proceedings of the 2009 International Conference on Reconfigurable Computing and FPGAs
High-speed FPGA-based implementations of a genetic algorithm

SAMOS'09 Proceedings of the 9th international conference on Systems, architectures, modeling and simulation
Customizable FPGA IP core implementation of a general-purpose genetic algorithm engine

IEEE Transactions on Evolutionary Computation

Critical Rays Scan Match SLAM

Journal of Intelligent and Robotic Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

One of the main tasks of a mobile robot in an unknown environment is to build and update a map of the environment and simultaneously determine its location within this map. This problem is referred to as the simultaneous localization and mapping (SLAM) problem. The article introduces scan-matching genetic SLAM (SMG-SLAM), a novel SLAM algorithm. It is based on a genetic algorithm that uses scan-matching for gene fitness evaluation. The main scope of the article is to present a hardware implementation of SMG-SLAM using an field programmable gate array (FPGA). The architecture of the system is described and it is shown that it is up to 14.83 times faster compared to the software algorithm without significant loss in accuracy. The proposed implementation can be used as part of a larger system, providing efficient SLAM for autonomous robotic applications.