The paper presents connections between the criteria which make three types of objects possible to be recognized, namely, edges, planes and corners. These criteria can be applied while a binaural sonar system is used. It is shown that the criteria are specific forms of a general equation. The form of the equation depends on a single coefficient. In the paper, the meaning of this coefficient is discussed. The constructions of the arrangement of objects are presented and are bound with values of the coefficient.
@article{bwmeta1.element.bwnjournal-article-amcv26i1p123bwm,
author = {Bogdan Kreczmer},
title = {Connections between object classification criteria using an ultrasonic bi-sonar system},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {26},
year = {2016},
pages = {123-132},
zbl = {1336.94010},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv26i1p123bwm}
}
Bogdan Kreczmer. Connections between object classification criteria using an ultrasonic bi-sonar system. International Journal of Applied Mathematics and Computer Science, Tome 26 (2016) pp. 123-132. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv26i1p123bwm/
[000] Adib, F. and Katabi, D. (2013). See through wall with Wi-Fi, ACM SIGCOMM'13, Hong Kong, China, pp. 75-86.
[001] Barshan, B. (1999). Location and curvature estimation of spherical targets using multiple sonar time-of-flight measurements, IEEE Transactions on Instrumentation and Measurement 48(6): 1212-1223.
[002] Barshan, B. and Kuc, R. (1990). Differentiating sonar reflections from corners and planes by employing an intelligent sensor, IEEE Transactions on Pattern Analysis and Machine Intelligence 12(6): 560 - 569.
[003] Bozma, O. and Kuc, R. (1991). Building a sonar map in a specular environment using a single mobile sensor, IEEE Transactions on Pattern Analysis and Machine Intelligence 13(12): 1260-1269.
[004] Brown, M.K. (1985). Feature extraction techniques for recognizing solid objects with an ultrasonic range sensor, IEEE Journal of Robotics and Automation 1(4): 191-205.
[005] Heale, A. and Kleeman, L. (2001). Fast target classification using sonar, 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, HI, USA, Vol. 3, pp. 1446-1451.
[006] Jackson, J.C., Summan, R., Dobie, G.I., Whiteley, S.M., Pierce, S.G. and Hayward, G. (2013). Time-of-flight measurement techniques for airborne ultrasonic ranging, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 60(2): 343-355.
[007] Kleeman, L. (2002). On-the-fly classifying sonar with accurate range and bearing estimation, IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, Vol. 1, pp. 178-183.
[008] Kleeman, L. (2004). Advanced sonar with velocity compensation, International Journal of Robotics Research 23(2): 111-126.
[009] Kleeman, L. and Kuc, R. (1994). An optimal sonar array for target localization and classification, IEEE International Conference on Robotics and Automation, San Diego, CA, USA, pp. 3130-3135.
[010] Kleeman, L. and Kuc, R. (1995). Mobile robot sonar for target localization and classification, International Journal of Robotics Research 14(4): 295-318.
[011] Kreczmer, B. (2010). Objects localization and differentiation using ultrasonic sensors, in H. Yussof (Ed.), Robot Localization and Map Building, InTech, Rijeka, pp. 521-543.
[012] Kreczmer, B. (2013). Relations between classification criteria of objects recognizable by ultrasonic systems, 16th IEEE International Conference MMAR 2011, Międzyzdroje, Poland, pp. 806-811.
[013] Kuc, R. and Siegel, M. (1987). Physically based simulation model for acoustic sensor robot navigation, IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI9(6): 766-778.
[014] Leonard, J.J. and Durrant-Whyte, H.F. (1991). Mobile robot localization by tracking geometric beacons, IEEE Transactions on Robotics and Automation 7(3): 376-382.
[015] Leonard, J.J. and Durrant-Whyte, H.F. (1992). Directed Sonar Sensing for Mobile Robot Navigation, Kluwer Academic Publishers, Boston, MA/London/Dordrecht. | Zbl 0760.68008
[016] Möller, M.M. (1995). Autonomous mobility with triaural sonar system, International Symposium on Intelligent Robotic Systems, Pisa, Italy, pp. 25-30.
[017] Nanani, G.K. and Prasad, K.M.V.V. (2013). A study of wi-fi based system for moving object detection through the wall, International Journal of Computer Applications 79(7): 15-18.
[018] Peremans, H., Audenaert, K. and Campenhout, J.M.V. (1993). A high-resolution sensor based on tri-aural perception, IEEE Transactions on Robotics and Automation 9(1): 36-48.
[019] Peremans, H., Campengout, J.V. and Levrouw, L. (1991). Steps towards tri-aural perception, in P.S. Schenker (Ed.), Sensor Fusion IV: Control Paradigms and Data Structures, SPIE, Bellingham, WA, pp. 165-176.
[020] Queirós, R., Corrêa Alegria, F., Silva Girão, P. and Cruz Serra, A. (2010). Cross-correlation and sine-fitting techniques for high-resolution ultrasonic ranging, IEEE Transactions on Instrumentation and Measurement 59(12): 1-10.
[021] Rencken, W.D., Peremans, H. and Möller, M. (1994). Tri-aural versus conventional sonar localisation and map building, JAS-4 Conference, Karlsruhe, Germany, pp. 398-402.