Simple but Novel Test Method for Quantitatively Comparing Robot Mapping Algorithms Using SLAM and Dead Reckoning

摘要

This article presents a comparative study between a well-known SLAM (Simultaneous Localization and Mapping) algorithm, called Gmapping, and a standard Dead-Reckoning algorithm; the study is based on experimental results of both approaches by using a commercial skid-based turning robot, P3DX. Five main base-case scenarios are conducted to evaluate and test the effectiveness of both algorithms. The results show that SLAM outperformed the Dead Reckoning in terms of map-making accuracy in all scenarios but one, since SLAM did not work well in a rapidly changing environment. Although the main conclusion about the excellence of SLAM is not surprising, the presented test method is valuable to professionals working in this area of mobile robots, as it is highly practical, and provides solid and valuable results. The novelty of this study lies in its simplicity. The simple but novel test method for quantitatively comparing robot mapping algorithms using SLAM and Dead Reckoning and some applications using autonomous robots are being patented by the authors in U.S. Patent Application Nos. 13/400,726 and 13/584,862.