Customized fastSLAM algorithm: analysis and assessment on real mobile platform

• Published in: Nonlinear dynamics Vol. 110; no. 1; pp. 669 - 691
• Main Authors: Maziarz, Bartosz, Domański, Paweł D.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2022; Springer Nature B.V
• Subjects: Algorithms; Automotive Engineering; Autonomous navigation; Classical Mechanics; Communication; Control; Decomposition; Dynamical Systems; Engineering; Kalman filters; Localization; Mechanical Engineering; Original Paper; Real time operation; Robots; Sensors; Simulation; Simultaneous localization and mapping; Unknown environments; Vibration; Split–merge algorithm; Real environment assessment; FastSLAM; Custom lidar; GPC; Localization; Extended Kalman filter; Particle filter
• ISSN: 0924-090X; 1573-269X
• DOI: 10.1007/s11071-022-07633-x

The task of simultaneous localization and mapping (SLAM) allows a mobile robot to localize itself in the unknown environment, while building the map of the surrounding landscape. It is frequently used for the navigation of autonomous mobile robots. Despite the fact that there are plenty available solutions, real applications encounter various application constraints. The present work addresses the subject of the modified fastSLAM application using custom lidar as the detection sensor. Available localization solutions are assessed, their constraints are identified and corresponding solutions are proposed. The algorithm is implemented, tested using simulations and finally applied to the existing mobile platform. Its validation considers various practical aspects of its operation in real-time environment.