<![CDATA[Many of researches in SLAM are targeting desktops or laptop computers. Mounted in a robot platform such as Pioneer, these high computational power hardware do all the processing in SLAM. Still others, SLAM algorithms exploit GPU power to provide deep details in map reconstruction. Yet, it is desirable to deploy SLAM in a small robot without advantages from high computational power hardware. Single board computer with limited power supply and low computational power is frequently the main board available in a small robot. Therefore, it is important to consider the design solution of SLAM that targets such a system. With this in mind, current work presents a survey paper of SLAM in low-resource hardware. The main question to be answered with this current work is "How researchers deal with hardware limitation when implementing SLAM?" Classification based on a method to tackle the problem is presented as the conclusion of this paper.]]>
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