Surface profile determination from multiple sonar data using morphological processing

In this thesis, a novel method for surface profile determination using multiple sensors is presented. Our approach is based on morphological processing techniques to fuse the range data from multiple sensor returns in a manner that directly reveals the target surface profile. The method has the intrinsic ability of suppressing spurious readings due to noise, crosstalk, and higher-order reflections, as well as processing multiple reflections informatively. The approach taken is extremely flexible and robust, in addition to being simple and straightforward. It can deal with arbitrary numbers and configurations of sensors as well as synthetic arrays. The profil of any continuous surface with varying curvature can be extracted as long as the curvature of the surface is not too high. The average processing time of the method is of the order of several seconds indicating that the method is viable for real-time applications. The algorithm is verified both by simulations and experiments in the laboratory by processing real sonar data obtained from the Nomad 200 mobile robot. The results are compared to those obtained from a more accurate structured-light system, which is however more complex and expensive.