Perception of an indoor robot workspace by using CTFM sonar imaging

Politis, Z.; Probert, P.J.

doi:10.1109/robot.1998.680475

Cited by 12 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is usually a complex function related to frequency f , distance r, and angle . 12) The echo signal was demodulated by multiplying the transmitted signal as…”

Section: Chirp Signalmentioning

confidence: 99%

Human Face Classification Using Ultrasonic Sonar Imaging

Miao

et al. 2009

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

In this paper, human face classification using ultrasonic sonar imaging is investigated. On the basis of Freedman's ''image pulse'' model, the scattering centers model is employed to simplify the complex geometry of the human face into a series of scattering centers. A chirp signal is utilized to detect the human face for its high range resolution and large signal-to-noise ratio. Ultrasonic sonar images, also named high-resolution range profiles, are obtained by demodulating the echoes with a reference chirp signal. Features directly related to the geometry of the human face are extracted from ultrasonic sonar images and verified in the experiments designed with different configurations of transmitter-receiver (TR) pairs. Experimental results indicate that the improved feature extraction method can achieve a high recognition rate of over 99% in the case of ultrasonic transmitters angled at 45 above and orthogonal to the face, and this method improves the performance of ultrasonic face recognition compared with our previous result.

show abstract

“…It is usually a complex function related to frequency f , distance r, and angle . 12) The echo signal was demodulated by multiplying the transmitted signal as…”

Section: Chirp Signalmentioning

confidence: 99%

Human Face Classification Using Ultrasonic Sonar Imaging

Miao

et al. 2009

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

show abstract

“…Ultrasonic ranging sensors have been widely used in collision avoidance [1], navigation [2,3], mapping [4,5], target classification [6,11], and in travel aid devices for visually impaired individuals [7,8]. The ultrasonic ranging sensor, which is low cost, accurate in positioning, and easy to operate, is considered as a competitive choice for implementing target detection and recognition.…”

Section: Introductionmentioning

confidence: 99%

“…With its advantages of high precision, broadband, high signal-to-noise ratio, and high quantity of information, the CTFM sonar is capable of detecting multiple targets, classifying primitive indoor targets [11], and even recognizing complex targets such as rough surfaces [12], leafy plants [13], and human faces [14]. However, most of the applications of a CTFM sonar are carried out under stationary conditions.…”

Section: Introductionmentioning

confidence: 99%

Continuous Transmission Frequency Modulation Detection under Variable Sonar-Target Speed Conditions

Wang

Yang

2013

Sensors

View full text Add to dashboard Cite

As a ranging sensor, a continuous transmission frequency modulation (CTFM) sonar with its ability for range finding and range profile formation works effectively under stationary conditions. When a relative velocity exists between the target and the sonar, the echo signal is Doppler-shifted. This situation causes the output of the sensor to deviate from the actual target range, thus limiting its applications to stationary conditions only. This work presents an approach for correcting such a deviation. By analyzing the Doppler effect during the propagation process, the sensor output can be corrected by a Doppler factor. To obtain this factor, a conventional CTFM system is slightly modified by adding a single tone signal with a frequency that locates out-of-sweep range of the transmitted signal. The Doppler factor can be extracted from the echo. Both verification experiments and performance tests are carried out. Results indicate the validity of the proposed approach. Moreover, ranging precision under different processing setups is discussed. For adjacent multiple targets, the discrimination ability is influenced by displacement and velocity. A discrimination boundary is provided through an analysis.

show abstract

“…The amplitude profile can therefore be used as the basis for robust extraction of primitives for map generation (Politis and Probert 1998). There is the potential for handling and distinguishing rough as well as smooth targets.…”

Section: Introductionmentioning

confidence: 99%

“…The advantages of the sensor lie in the higher power transmitted because the sensor operates continuously rather than in pulsed mode, and in the Fourier transform, which performs significant averaging and hence noise reduction. The amplitude profile can therefore be used as the basis for robust extraction of primitives for map generation (Politis and Probert 1998). There is the potential for handling and distinguishing rough as well as smooth targets.…”

Section: Introductionmentioning

confidence: 99%

Feature Extraction from a Broadband Sonar Sensor for Mapping Structured Environments Efficiently

Kao

Probert

2000

The International Journal of Robotics Research

View full text Add to dashboard Cite

In this paper, we describe the use of a broadband, frequencymodulated sonar sensor (a CTFM sonar) for generating maps of structured environments for robots and autonomous systems. The major advantage of using these sensors is that the information generated is reliable enough to extract the geometry and type of certain features with very few measurements; hence, maps can be generated rapidly. Although the technology of low-cost CTFM sonar has been available for some time, it has only very recently been considered seriously as a candidate sensor for navigation and mapping in spite of its superior performance. We describe the operation of the sensor and the use of both the range-orientation and amplitude-orientation profiles to extract information online and point targets in both smooth and rough environments. We demonstrate the method through generating a map for a room typical of a modern building (in fact, in a domestic house), using resolution of scanning increment from 1.8 deg down to 10.8 deg. We examine the robustness of the method as the number of measurements is reduced through introducing two quality metrics for each map.

show abstract

Perception of an indoor robot workspace by using CTFM sonar imaging

Cited by 12 publications

References 5 publications

Human Face Classification Using Ultrasonic Sonar Imaging

Human Face Classification Using Ultrasonic Sonar Imaging

Continuous Transmission Frequency Modulation Detection under Variable Sonar-Target Speed Conditions

Feature Extraction from a Broadband Sonar Sensor for Mapping Structured Environments Efficiently

Contact Info

Product

Resources

About