A survey on sensing methods and feature extraction algorithms for SLAM problem
It provides a comparative analysis for researchers designing SLAM systems, but it is incremental as it reviews existing methods without introducing new techniques.
This survey compares sensing methods and feature extraction algorithms for SLAM robots to generate 3D dense maps in unknown unstructured environments, aiming to identify the best options for a larger project.
This paper is a survey work for a bigger project for designing a Visual SLAM robot to generate 3D dense map of an unknown unstructured environment. A lot of factors have to be considered while designing a SLAM robot. Sensing method of the SLAM robot should be determined by considering the kind of environment to be modeled. Similarly the type of environment determines the suitable feature extraction method. This paper goes through the sensing methods used in some recently published papers. The main objective of this survey is to conduct a comparative study among the current sensing methods and feature extraction algorithms and to extract out the best for our work.