首页 /研究 /A Systematic Mapping Study on Multi-Sensor Fusion in Wheeled Mobile Robot Self-Localization
PERCEPTION

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

Carlos Eduardo Magrin, Robison Cris Brito, Eduardo Todt

发表年份
2019
引用次数
7

摘要

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.

关键词

Mobile robotSensor fusionComputer scienceRobotEncoderKalman filterComputer visionArtificial intelligenceFusionSimultaneous localization and mapping

相关论文

查看 PERCEPTION 分类全部论文