3D shape recognition system by ultrasonic sensor array and genetic algorithms

Baba, Mitsuru; Ohtani, Kozo; Komatsu, Setsuko

doi:10.1109/imtc.2004.1351468

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Two years later, they developed their work and introduced a 3D diagnostic system based on a genetic algorithm and the rotation of a one-dimensional array of ultrasonic sensors around a target object. The results of these experiments were more favorable in the research dimension than the previous method, but due to the rotation of the sensor array around the cylinder, it had limited practical implementation and by changing the dimensions of the target object, the rotation radius also increased (Baba, Ohtani et al 2004) [9]. However many problems in recognizing the position and shape of objects still remain.…”

Section: Introductionmentioning

confidence: 94%

Ultrasonic System to Improve Position Measurement and Shape Recognition Based on Neural Network

Hadadi¹

2021

CRPASE

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Today, with the advancement of technology, the use of remote detection systems in various fields of medicine, industry and robotics has become common. In this regard, accurate recognition of the position and shape of objects is one of the main concerns. Guidance systems for the blind, car parking, separation systems and intelligent robots are examples of these systems. The basis of these systems is based on one of the methods of image processing, infrared or ultrasound. In this paper, the researchers have dealt with a method that has high diagnostic accuracy at a low cost and is resistant to environmental conditions. The proposed method consists of two phases: position recognition and shape recognition. In the first phase, the exact position of the object is calculated using the laws of wave physics and the method known as the improved time of flight method. In the second phase, a set of ultrasonic sensors with a two-dimensional matrix arrangement and a neural network were used to detect the shape of the object. In the first phase, the average distance detection error decreased from 1.875, which was related to the time of flight method, to 0.271. In the second phase, the efficiency of the neural network was 96.8 and the error rate was 3.2. The system presented in both phases is very low cost and is associated with increased measurement accuracy, which can therefore be a good alternative to other methods.

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Section: Introductionmentioning

confidence: 94%

Ultrasonic System to Improve Position Measurement and Shape Recognition Based on Neural Network

Hadadi¹

2021

CRPASE

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“…That complicates too much for direct use of sonar data for object recognition or topological localization. An well-known way to solve these problems is using neural networks [7], [8], [9], genetic algorithms [10], Fuzzy Artmap [11], Hough transform [12] or an extended Kalman filter [13]. Researches involved the analysis of a two objects based on Continuously Transmitted Frequency Modulated ultrasonic sensor [14].…”

Section: Related Workmentioning

confidence: 99%

Identification Effectiveness of the Shape Recognition Method Based on Sonar

Dimitrova-Grekow

Jarczewski

2015

Computer Information Systems and Industrial Management

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Part 4: Data Analysis and Information RetrievalInternational audienceSonars are among the most popular navigation elements used in autonomous vehicles. Beside their well known properties, they have unexplored specifics offering interesting information. In this paper, we present the results of an experiment with the drawbacks of sonars. Our approach combined the regular information obtained from a sonar system with information deriving from measurement aberration. The experiments with an ultrasonic range measurement system of a mobile robot showed that the usually neglected sonar drawbacks could be unusually helpful. This paper emphasizes the effectiveness of identification, which was calculated based on the ratio of the quantities of parallelepipeds to cylinders. The experimental results are presented. Further work aims to implement this idea on a robot on an HCR base. Another possibility is also suitable implementation of map building with a relative degree of confidence

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“…From Fig. 5, it can be seen that (2) where and are the perpendicular distances of object points (see Fig. 5) and is the spacing distance between photodiodes and LEDs on the sensor board.…”

Section: A Sensor Modelmentioning

confidence: 99%

“…Despite their accuracy, their size and price present a serious drawback. Traditional distance measurement sensors such as ultrasonic and infrared Position Sensing Devices could also be used for creating 3D images of an object [1], [2]. Ultrasonic (US) and offset-based infrared Position Sensing Devices (PSD) are widely used in order to determine the distance of an object.…”

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confidence: 99%

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Object Outline and Surface-Trace Detection Using Infrared Proximity Array

Tar

Cserey

2011

IEEE Sensors J.

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In this paper, a method of detecting object outlines and creating surface traces using a low-cost distance measurement array of infrared light-emitting diode (LED)-photodiode pairs is demonstrated. For each active LED, the light level on the corresponding photodiode may be measured, generating an image of distance values whose pixel resolution is limited to the spacing between LED-photodiode pairs. Moreover, using several photodiodes to detect the reflected light from each LED, lateral resolution is enhanced, and the angle of reflection can also be detected. Experimental results demonstrate successful application of such data to detecting object outlines and surfaces, and show promising possibilities in using the array for simultaneous localization and mapping (SLAM). The developed sensor array is best suited for environments where prior information of object distance is available (e.g., production lines), or where only relative distance information is needed. In addition, the speed and low cost of the array makes it a good supplementary device to more precise, yet at the same time slower and more expensive distance measurement devices.Index Terms-Distance measurement, infrared imaging, infrared measurement, object detection.

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3D shape recognition system by ultrasonic sensor array and genetic algorithms

Cited by 6 publications

References 8 publications

Ultrasonic System to Improve Position Measurement and Shape Recognition Based on Neural Network

Ultrasonic System to Improve Position Measurement and Shape Recognition Based on Neural Network

Identification Effectiveness of the Shape Recognition Method Based on Sonar

Object Outline and Surface-Trace Detection Using Infrared Proximity Array

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