Sensors, SLAM and Long-term Autonomy: A Review
Mubariz Zaffar, Shoaib Ehsan, Rustam Stolkin, Klaus McDonald Maier
TL;DR
This review paper discusses various sensors used in SLAM, evaluates their characteristics for long-term autonomy, and compares their suitability for robotic applications over extended periods.
Contribution
It provides a comprehensive comparison of sensors for SLAM and assesses their long-term autonomy capabilities, highlighting future challenges and considerations.
Findings
Different sensors have unique strengths and limitations for SLAM.
Sensor selection critically impacts long-term autonomous robot performance.
The paper identifies key factors influencing sensor effectiveness over time.
Abstract
Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades. For solving the SLAM problem, every robot is equipped with either a single sensor or a combination of similar/different sensors. This paper attempts to review, discuss, evaluate and compare these sensors. Keeping an eye on future, this paper also assesses the characteristics of these sensors against factors critical to the long-term autonomy challenge.
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