Abstract
A novel, simple and efficient method for vision based range measurements with uncalibrated cameras is presented. Required parameters are the image size, the relative distance between two different image frames of the same scene and the field of view of the camera(s). Range measurements acquired using ultrasonic sensors and a vision system have been used to navigate a mobile robot around known colored obstacles in an indoor environment. Both sonar sensors and cameras are activated and they operate simultaneously in parallel to obtain range measurements from common search areas located in the front of the mobile robot. Experimental results using a parallel stereoscopic, rotated and monocular vision system with uncalibrated cameras confirm that the maximum computational error (as well as the normalized root mean square error) of range measurements using the vision system for obstacles lying at a distance of 27–800 cm from the robot, is smaller compared to other similar, even more advanced and state-of-the-art existing approaches, reported in Rajagopalan (IEEE Trans. Pattern Anal. Mach. Intell., 28(11): 1521–1525, 2004), Mudenagudi and Chaudhuri (Proceedings of IEEE International Conference on Computer Vision, 1: 483–488, 1999), Umeda and Takahashi (Proceedings of IEEE ICRA, pp. 3215–3220, April 2000), Jiang and Weymouth (Proceedings of IEEE CVPR, pp. 250–255, June 1989), Lai, Fu, and Chang (IEEE Trans. Pattern Anal. Mach. Intell., 14(4):405–411, 1992), Malis and Rives (Proceedings of IEEE ICRA, pp. 1056–1061, 2003), Derrouich, Izumida, and Shiiya (IEEE Annual Conference on IECON, 3: 2191–2196, Nov. 2002).
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References
Ohya, A., Kosaka, A., Kak, A.: Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing. IEEE Trans. Robot. Autom. 14(6), 969–978 (December 1998)
Duffy, B.R., Garcia, C., Rooney, C.F.B, O’Hare, G.M.P.: Sensor fusion for social robotics. In: 31st International Symposium on Robotics, Montréal, Canada, pp. 258–264, May 2000
Mann, R., Jones, J., Beckerman, M., Glover, C., Farkas, L., Han, J., Wacholder, E., Einstein, J.: An intelligent integrated sensor system for the ORNIL mobile robot. In: Proceedings of IEEE on Intelligent Control, pp. 170–173 (1988)
Gubber, G., Sahli, H.: Sensor integration on a mobile robot. In: 12th International Symposium on Measurement and Control in Robotics, France, June 2002
Rajagopalan, A.N.: Depth estimation and image restoration using defocused stereo pairs. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1521–1525 (November 2004)
Mudenagudi, U., Chaudhuri, S.: Depth estimation using defocused stereo image pairs. In: Proceedings of IEEE International Conference on Computer Vision, vol. 1, 483–488, September 1999
Umeda, K., Takahashi, T.: Subpixel stereo method: a new methodology of stereo vision. In: Proceedings of IEEE ICRA, pp. 3215–3220, April 2000
Jiang, F., Weymouth, T.E.: Depth from dynamic stereo images. In: Proceedings of IEEE CVPR, pp. 250–255, June 1989
Lai, S-H., Fu, C-W., Chang, S.: A generalized depth estimation algorithm with a single image. IEEE Trans. Pattern Anal. Mach. Intell 14(4), 405–411 (April 1992)
Malis, E., Rives, P.: Robustness of image-based visual servoing with respect to depth distribution errors. In: Proceedings of IEEE ICRA, pp. 1056–1061, 2003
Derrouich, S., Izumida, K., Shiiya, K.: A combination of monocular CCD camera and inertial-sensor for range estimation. In: IEEE Annual Conference on IECON, vol. 3, pp. 2191–2196, November 2002
Fox, D., Burgard, W., Thrun, S.: The dynamic window approach to collision avoidance. IEEE Robot. Autom. Mag. 4(1), 23–33 (March 1997)
Sahin, E., Gaudiano, P.: Mobile robot range sensing through visual looming. In: Proceedings of IEEE ISIC, pp. 370–375, September 1998
CCIR. Encoding parameters of digital television for studios. CCIR Recommendation 601-2, International Radio Consultative Committee (ITU), 1990
Dios, J.J., Garcia, N.: Face detection based on a new color space YCgCr. In: International Conference on Image Processing, vol. 3, pp. III 909–12, vol 2, 2003
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading, MA (1992)
Jain, R., Kasturi, R., Schunck, B.G.: Machine Vision. McGraw-Hill, New York (1995)
Doitsidis, L., Valavanis, K.P., Tsourveloudis, N.: Fuzzy logic based autonomous skid steering vehicle navigation. In: Proceedings of IEEE ICRA, pp. 2171–2177, May 2002
Jennings, A., Murray, D., Little, J.J.: Cooperative robot localization with vision-based mapping. In: Proceedings of IEEE ICRA, vol 4, pp. 2659–2665, May 1999
Recken, W.D.: Autonomous sonar navigation in indoor, unknown and ustructured environments. In: Proceedings of IEEE IROS, vol 1, pp. 431–438, September 1994
Elfes, A.: Sonar-based real world mapping and navigation. IEEE J. Robot. Autom. 3, 249–265 (June 1987)
Valavanis, K.P., Hebert, T., Kolluru, R., Tsourveloudis, N.: Mobile robot navigation in 2-D dynamic environments using an electrostatic potentional field. IEEE SMC 30, 187–196 (March 2000)
Tucakov, V., Sahota, M., Murray, D., Mackworth, A., Little, J., Kingdom, S., Jennings, C., Barman, R.: Spinoza: a stereoscopic visually guided mobile robot. In: Proceedings of 30th ICSS, vol. 5, pp. 188–197, January 1997.
Russ, J.C.: The Image Processing Handbook. CRC Press, Boca Raton, FL (1995)
Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis and Machine Vision. PWS Publishing, New York (1999)
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Tsalatsanis, A., Valavanis, K. & Tsourveloudis, N. Mobile Robot Navigation Using Sonar and Range Measurements from Uncalibrated Cameras. J Intell Robot Syst 48, 253–284 (2007). https://doi.org/10.1007/s10846-006-9095-8
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DOI: https://doi.org/10.1007/s10846-006-9095-8