Sonar Signal Processing using Tangent Clusters

Robert Mandelbaum Max Mintz General Robotics and Active Sensory Perception (GRASP) Laboratory Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104 Abstract We describe a novel approach to the extraction of geometric features from sonic data. As is well known, a single sonar measurement using a standard PolaroidTM sensor, though yielding relatively accurate information regarding the range of a re ective surface patch, provides scant information about the location in azimuth or elevation of that patch. This lack of su ciently precise localization of the reective patch hampers any attempt at data association, clustering of multiple measurements or subsequent classi cation and inference. The problem is particularly apparent in uncertain environments with unknown geometry, such as is found underwater. Moreover, the underwater environment precludes the usual (o ce-environment) simpli cation of two-dimensionality. We propose a multi-stage approach to clustering which aggregates sonic data accumulated from arbitrary transducer locations in an on-line fashion. It is computationally tractable and e cient despite the inherent exponential nature of clustering, and is robust in the face of noise in the measurements. It therefore lends itself to applications where the transducers are xed relative to the mobile platform, where remaining stationary during a scan is both impractical and infeasible, and where deadreckoning errors can be substantial. The approach may be used both for map-building during exploration and for feature identi cation during navigation.