J.P. Oria

Ultrasonic Sensors in Urban Traffic Driving-Aid Systems

Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, most of which occur in urban environments. The most prominent include Antilock Braking Systems (ABS), Traction Control and Stability Control. All these systems use different kinds of sensors to constantly monitor the conditions of the vehicle, and act in an emergency. In this paper the use of ultrasonic sensors in active safety systems for urban traffic is proposed, and the advantages and disadvantages when compared to other sensors are discussed. Adaptive Cruise Control (ACC) for urban traffic based on ultrasounds is presented as an application example. The proposed system has been implemented in a fully-automated prototype vehicle and has been tested under real traffic conditions. The results confirm the good performance of ultrasonic sensors in these systems.

Fuzzy expert system with double knowledge base for ultrasonic classification

Abstract This article shows a pattern recognition method for object classification using ultrasonic sensors and a dual knowledge base fuzzy expert system. The developed system uses a pair of ultrasonic sensors for obtaining information about the object shape from the ultrasonic echo signal envelope. In order to reduce the size of the database, a set of parameters is calculated for extracting knowledge about the object. However, the information provided by ultrasonic sensors contains a very high uncertainty level. This uncertainty is caused by several environmental effects, which are very difficult to eliminate in industrial applications. Among these environment factors are the air temperature and humidity, the air movement, etc. They create variations in the proprieties of the medium and disturbances during the acoustic propagation process. The presented system has been specially designed for industrial applications, where it is very difficult to reduce these disturbances and where it is necessary to use intelligent systems with high autonomy. The fuzzy expert system proposed has a dual knowledge base, that is, a statistical knowledge located on the memberships functions, and the standard rule-based knowledge. This expert system deals with the uncertainties in the information, and it is able to generate and modify the knowledge base and the decision rules in an automatic way. Furthermore, it is able to adapt the knowledge base to the slow changes produced by disturbing factors, such as humidity and temperature. On the other hand, because this system maintains a rule-based structure it is very easy to incorporate expert human knowledge.

Three Dimensional Ultrasonic Vision of Surfaces for Robotic Applications

Abstract This article deals with the utilisation of ultrasonic sensor airays as an artificial vision system for robotics applications. This array will be placed on the robot grip in such a way that it will be possible to detect the presence of an object, to direct the robot tool towards it and to locate the object position. Furthermore, it will provide visual information about the surface by means of the echo-signal technique. A possible structure for the vision system is presented.

Three-Dimensional Robotic Vision Using Ultrasonic Sensors

This article describes a three-dimensional artificial vision system for robotic applications using an ultrasonic sensor array. The array is placed on the robot grip so that it is possible to detect the presence of an object, to direct the robot tool towards it, and to locate the object position. It will provide visual information about the objects surface by means of superficial scanning and it permits the object shape reconstruction. The developed system uses an approximation of the ultrasonic radiation and reception beam shape for calculating the first contact points with the objects surface. On the other hand, the position of the arrays sensors has been selected in order to provide the sensorial head with other useful capabilities, such as edge detection and edge tracking. Furthermore, the article shows the structure of the sensorial head for avoiding successive rebounds between the head and the object surface, and for eliminating the mechanical vibrations among sensors.

Pattern recognition with ultrasonic sensors: a neural networks evaluation

This paper presents an evaluation of several types of neural networks for object recognition by means of ultrasonic sensors. Initially, in order to obtain information from the ultrasonic signal, a parametric method is proposed and a set of features is extracted from the ultrasonic echo envelope. Then, it is necessary to evaluate how much information is provided for each characteristic obtained. Therefore, it has been necessary to carry out an analysis in order to detect the most relevant features. Results about information provided for each feature are presented by order of preference. Subsequently, using these features extracted from the echo signal, an experimental set‐up has been carried out in order to highlight the capabilities of different types of neural networks with this information. Finally, results obtained from experimental tests are presented, and the pattern recognition capabilities of each neural network type, using the selected features, are shown.

Accurate Estimation of Airborne Ultrasonic Time-of-Flight for Overlapping Echoes

In this work, an analysis of the transmission of ultrasonic signals generated by piezoelectric sensors for air applications is presented. Based on this analysis, an ultrasonic response model is obtained for its application to the recognition of objects and structured environments for navigation by autonomous mobile robots. This model enables the analysis of the ultrasonic response that is generated using a pair of sensors in transmitter-receiver configuration using the pulse-echo technique. This is very interesting for recognizing surfaces that simultaneously generate a multiple echo response. This model takes into account the effect of the radiation pattern, the resonant frequency of the sensor, the number of cycles of the excitation pulse, the dynamics of the sensor and the attenuation with distance in the medium. This model has been developed, programmed and verified through a battery of experimental tests. Using this model a new procedure for obtaining accurate time of flight is proposed. This new method is compared with traditional ones, such as threshold or correlation, to highlight its advantages and drawbacks. Finally the advantages of this method are demonstrated for calculating multiple times of flight when the echo is formed by several overlapping echoes.

Evaluation of expert systems for automatic shape recognition by ultrasound

This paper presents an evaluation of several types of expert systems in automatic object recognition for robotic manipulators, using ultrasound. In fact, rule-based expert systems and probabilistic expert systems have been compared in a calculation of prismatic body orientation and object shape recognition. Furthermore, both types of expert systems were used to distinguish different piece shapes and to detect object position in a real scenario using a robotic manipulator. Information for the automatic recognition system is provided to the expert system by means of the ultrasonic signal coming back from the illuminated object, which is captured by only one receiver placed on the robot grip. Subsequently, in order to reduce the number of parameters to work with, a parametric method for characterisation of this signal is presented. This has been done by calculating several geometric parameters from the signal envelope. Afterwards, a study of the probability distribution function for each parameter provides the necessary information for the expert system to carry out the distinction between the different objects of interest. In this way, it permits the establishment of a comparison among different expert system types for automatic shape recognition using ultrasounds.

Automatic fault detection using ultrasonic techniques: expert system vs. signal processing

In general, ultrasonic sensors are used in environments where there can be hostile conditions which impede the successful use of other methods such as artificial vision. When this occurs, ultrasonic sensors can be used in order to check for the existence of fabrication defects in foundry pieces before allowing them to be machined. This check is carried out by studying the echoes coming from the piece under analysis. This article is based on the comparison of the results obtained from two analysis techniques which use these echoes. Both systems work by differentiating the valid pieces from the defective ones, using the high part of the ultrasonic frequency range (215 kHz). In the first case, the process of separation of valid and defective pieces is based on expert systems, applied directly on the temporal characteristics of the echoes. For the second defect detection method, signal processing techniques are used on these high-frequency echoes; firstly, digitally filtering the signal and then, once the part of the signal pertaining to the echoes coming from the piece is separated, it is decomposed into its frequential components. The techniques used in these two working methods are explained in this article.

Short Distance Ultrasonic Vision for Mobile Robots

Abstract Using ultrasonic sensors it is possible to detect the presence of an object, to localise its position and to realise a superficial scanning in order to give information about the three dimensional shape of the piece. Consequently, it permits to endow the robot with a certain capacity of interaction with the environment. Besides, this could be used to provide a visual information to the robot operator or to supply this data to an artificial intelligent system. Important aspects such as radiation angle, edge detection and edge tracking are presented

Ultrasonic Robotic Vision Using Fuzzy Logic for Surface Reconstruction

Abstract This article deals with the utilisation of ultrasonic sensor arrays as artificial vision system for robotics applications. It will provide visual information about the surface by means of the echo-signal. A surface reconstruction method is shown. It is based on the information provided by the ultrasonic echo signal coming back from the object. Then, two fuzzy expert systems are used during the scanning process. The first one deals with the path planning and the second one takes charge of the decision taken process in order to improve the visual information.