Abstract
In the era of autonomous robot mapping, assessing the goodness of the generated maps is important, and is usually performed by first aligning them to blueprints and then calculating the displacement error. Accuracy of map alignment is also critical in other applications such as collaborative mapping in multi-robot applications and the use of prior maps in real time robot localization and navigation. However, map alignment is difficult for two reasons: first, one map can be significantly distorted from the other, and second, establishing what constitutes a ground truth for alignments of different types is challenging. Most map alignment techniques to this date have addressed the first problem, while paying too little importance to the second. In this paper, we propose a ground truth, which consists of synthetically transformed maps with their corresponding displacement fields. Furthermore, we propose a new system for comparison, where the displacement field of any map alignment technique can be computed and compared to the ground truth using statistical measures. The local information in displacement fields renders the evaluation system applicable to any alignment technique, whether it is linear or not. In our experiments, the proposed method was applied to different alignment techniques from the literature.