Abstract
Over the past two decades or so, robotics researchers have thoroughly investigated one of the fundamental problems in robotics commonly known as Simultaneous Localization and Mapping (SLAM). This is primarily a chicken-and-egg problem as the robot is supposed to navigate in an unknown environment (i.e., unknown map of target area) and it must know its own location at all times (i.e., localization). Both of these problems are to be solved simultaneously as the robot needs to know its location with respect to the map being generated and the map can only be generated by exploring, which requires the robot to know where it is and where it is headed. This chapter summarizes some of most noticeable works in this domain.
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