A Systematic Mapping Study on Multi-Sensor Fusion in Wheeled Mobile Robot Self-Localization

• Carlos Magrin UFPR
• Robison Brito UTFPR
• Eduardo Todt UFPR

Resumo

Sensor fusion is a well-explored area with constant research over the last thirty years for application in mobile robot localization. This systematic mapping study (SMS) identifies areas for more primary studies to be conducted. The goal of the study is to identify the main methods of sensor fusion and sensor types, aiming at application with multiple sensors in indoor and/or outdoor environments. As a result of the present study, it was observed a trend of applying vision, ultrasound, laser, and encoder in multi-sensor fusion systems. It's also remarkable that most systems use two kinds of sensors. Researches published in the last five years (2019) point to the Kalman filter as the predominant state-of-the-art sensor fusion method applied to wheeled mobile robot (WMR) localization. In this systematic study, we also identified which conferences have the largest number of multi-sensor fusion publications applied to mobile robots.

Palavras-chave: Robot sensing systems, Mobile robots, Sensor fusion, Systematics, Laser fusion, Kalman filters