Vision based SLAM for humanoid robots: A survey

Abstract

This paper is a survey work for designing a Vision based Simultaneous Localization and Mapping (VSLAM) humanoid robot to generate a map of an unknown environment. A lot of factors have to be considered while designing a VSLAM robot. Vision Sensors are very attractive for application in SLAM because of their rich sensory output and cost effectiveness. Different issues are involved in the problem of vision based SLAM and many different approaches exist in order to solve these issues. Similarly the type of environment determines the suitable feature extraction method. The main objective of this survey is to conduct a comparative study among the current vision sensing methods in terms of imaging systems used for performing VSLAM, feature extraction algorithms used in some recently published papers, and initialization of landmarks, and to figure out the best for our work.