Real world map building and localization through continuous sonar sensing and clustering

Map building in the real world using sonars poses two challenges: 1) noisy sonar readings which need sophisticated preprocessing; and 2) complicated floor plans which make it difficult to extract key features in the environment. We have developed a continuous sonar sensing and clustering method to solve the problems. The method allows us not only to discard sonar readings irrelevant for localization but also to extract key environment features that can be traced for some period of time. An important advantage of our method is that we do not need to register key environment features (i.e. landmark patterns) in advance. We have successfully implemented and tested a map building and localization system using the method. We report on our experiment conducted using a physical robot in an unmodified large scale environment