Simultaneous localization and mapping (SLAM) is a fundamental problem in mobile robotics. The ever growing number of landmarks during robot action is still a problem on the way to lifelong operation. The reason is that the continuously growing number of landmarks leads to an unbounded increase of computational complexity in terms of computational power and memory.

We present a novel approach to define the benefit of a landmark in SLAM to address bounded resources. The general idea of our approach is to remove landmarks with a low localization benefit. We keep landmarks such, that their observability regions cover the operational area. The rational behind this is that the position of a landmark itself does not give a hint on its usefulness for robot localization. However, ensuring landmark visibility within the operational area leads to a minimum localization quality in the whole operational area.

We compare our approach of handling landmarks against the standard approach without upper bound on the number of landmarks in real-world experiments. These experiments are performed on a P3DX-platform with a Visual SLAM approach.