Multi-echo technique for feature detection and identification using simple sonar configurations

This work presents the study and development of sonar sensor configurations and processing methods with capability to detect and identify planes, edges and corners. The systems presented can be easily applied to settled robots or new platforms to improve the quality and quantity of ultrasonic data. No special configurations as arrays or cells of sensors are used in this work, only standard configurations that can be found and applied in a great number of mobile robots. New multi-echo functionalities are introduced and combined with EERUF, providing a new ME-EERUF (Multi-Echo Error Eliminating Rapid Ultrasonic Firing) method that simultaneously increases the sonar acquisition rate and provides inter-sensor measurements, necessary to implement feature detection and identification algorithms. Sonar feature-based and grid-based maps are built and integrated online using Bayesian probabilistic approaches. Experimental results using data collected in a specular indoor environment are presented in the paper.