Utilisation des capteurs ultrasonores pour la distinction entre un plan et un coin à l'aide des méthodes statistiques

La technologie ultrasonore permet de développer un système de perception à faible coût pour la robotique de service. L'extraction des informations pertinentes sur l'environnement exige le traitement du signal ultrasonore. Les méthodes statistiques sont capables de discriminer des objets d'un environnement structuré, (plan, coin, etc...). La difficulté principale de la classification est le choix des paramètres discriminants du signal réfléchi par les cibles rencontrées. La dimension de l'espace de représentation des objets est réduite à l'aide de la méthode suboptimal. Les paramètres extraits définissent le vecteur d'entrée du classifieur quadratique. Les résultats obtenus montrent le taux de bonne classification par rapport à la dimension du vecteur d'entrée

An inverse model of ultrasonic echolocation

Object recognition systems based on ultrasonic sensing have significant drawbacks in generality, resolution and speed. The objective of our research was the development of more efficient technique(s) for ultrasonic based object recognition through the investigation of models of acoustic backscatter, with particular emphasis on the work of Albert Freedman. The �image pulse� model developed by Freedman calculates the echoes generated from convex objects in an underwater environment after insonification with a narrowband transient signal. The primary prediction of this model is that echoes are generated at those points along a scattering body where there are step discontinuities in the derivatives, with respect to range, of the solid angle subtended at the transducer by the scatterer, the amplitudes of the echoes being a linear combination of the magnitudes of said discontinuities. We extended this model for use in an air environment using non-coincident transmitters and receivers and conducted experiments to measure the amplitudes of the echoes from a range of radially symmetric convex objects, at distances up to 1.4m, after insonification with a Polaroid transducer. These amplitudes were compared to those predicted by the model, with the results for the cones highlighting the limitations of the theory at modelling the echoes from the geometrical shadow boundaries of objects. The results for the spherical objects were significantly better however, with an average error of less than 5%, suggesting that the model should be reasonably accurate at calculating the echoes from convex objects with smoothly varying surfaces. The extended forward model was then inverted to produce an inverse model that would calculate the geometrical parameters of a radially symmetric scattering body from an analysis of the echoes received after insonification of these bodies with ultrasonic pulses at two discrete frequencies. A quantitative verification of this inverse model with various scattering bodies proved elusive, with a low correlation between experiment and theory, due to matrix instability and difficulties in obtaining data of sufficient accuracy. However, qualitative trends in the data indicate that the model is essentially correct, though very sensitive to measurement precision and media characteristics, and there is good reason to believe that further work under more controlled laboratory conditions and/or a different medium would verify the model�s validity quantitatively. Finally, the inverse model was tested to see whether it could find a practical application despite its quantitative limitations. In many industries, quality control involves distinguishing between those items that are physically damaged and those that are not, a task that the inverse model may be able to address. Using glass bulbs as the test subjects, some with simulated physical damage and some without, we tested the ability of the inverse model to distinguish between these two classes of objects. In all cases, the model clearly separated the items with simulated damage from those without. The inverse model should be of interest to workers in the field of industrial quality control because of its potential to lead to the development of real-time inspection systems for production lines that could perform with a higher efficiency than the visual inspection procedures currently being employed

Sonar sensor interpretation for ectogeneous robots

We have developed four generations of sonar scanning systems to automatically interpret surrounding environment. The first two are stationary 3D air-coupled ultrasound scanning systems and the last two are packaged as sensor heads for mobile robots. Template matching analysis is applied to distinguish simple indoor objects. It is conducted by comparing the tested echo with the reference echoes. Important features are then extracted and drawn in the phase plane. The computer then analyzes them and gives the best choices of the tested echoes automatically. For cylindrical objects outside, an algorithm has been presented to distinguish trees from smooth circular poles based on analysis of backscattered sonar echoes. The echo data is acquired by a mobile robot which has a 3D air-coupled ultrasound scanning system packaged as the sensor head. Four major steps are conducted. The final Average Asymmetry-Average Squared Euclidean Distance phase plane is segmented to tell a tree from a pole by the location of the data points for the objects interested. For extended objects outside, we successfully distinguished seven objects in the campus by taking a sequence scans along each object, obtaining the corresponding backscatter vs. scan angle plots, forming deformable template matching, extracting interesting feature vectors and then categorizing them in a hyper-plane. We have also successfully taught the robot to distinguish three pairs of objects outside. Multiple scans are conducted at different distances. A two-step feature extraction is conducted based on the amplitude vs. scan angle plots. The final Slope1 vs. Slope2 phase plane not only separates the rectangular objects from the corresponding cylindrical