A visual regulation strategy based on a decoupled ego-motion estimation technique, is presented for a nonholonomic mobile robot. Ego-motion in a static environment can be robustly estimated by planar region alignment, which initially detects the 2D planar motion between two frames, and the 2D motion is used to align corresponding image regions. Such a 2D registration removes all effects of the camera rotation, and the resulting residual displacement between the two aligned images is an epipolar field centered at the FOE (Focus of Expansion). Then 3D camera translation is recovered from the epipolar field. The 3D camera rotation is then derived from the recovered 3D translation and the detected 2D motion. By this way, the ego-motion estimation is decoupled into a 2D parametric motion and residual epipolar parallax displacements, which avoids many of the inherent ambiguities and instabilities associated with decomposing the image motion into its rotational and translational components, and hence makes the computation of ego-motion or 3D structure estimation more robust. Based on the ego-motion estimation, an adaptive control law for visual regulation of nonholonomic mobile robot is presented and the stability of the close loop system is analyzed in the sense of Lyapunov stability theory. Experiments show that the convergence of the proposed visual regulation.
References
Hutchinson S, Hager GD, Corke PI. A tutorial on visual servo control. IEEE trans. on Robotics and Automation 1996; 12(5): 651-670. http://dx.doi.org/10.1109/70.538972
Malis E. Survey of vision-based robot control. European Naval Ship Design, Captain Computer IV Forum, ENSIETA, Brest France 2002; April 2002.
Espiau B. Effect of camera calibration errors on visual servoing in robotics. in Proc. 3rd Int. Symp. Exp. Robot 1993; 182-192.
Malis E, Chaumette F. Theoretical improvements in the stability analysis of a new class of model-free visual servoing methods. IEEE Trans Robot Autom 2002; 18(2): 176-186. http://dx.doi.org/10.1109/TRA.2002.999646
Malis E, Chaumette F, and Boudet S. 2-1/2-D visual servoing. IEEE Trans. Robot. Autom. 1999; 15(2): 238-250. http://dx.doi.org/10.1109/70.760345
Chaumette F, Hutchinson S. Visual Servo Control, Part I: Basic Approaches. IEEE Robotics and Automation Magazine 2006; 13(4): 82-90. http://dx.doi.org/10.1109/MRA.2006.250573
Chaumette F, Hutchinson S. Visual Servo Control, Part II: Advanced Approaches. IEEE Robotics and Automation Magazine 2007; 14(1): 109-118. http://dx.doi.org/10.1109/MRA.2007.339609
Masutani Y, Mikawa M, Maru N and Miyazaki F. Visual servoing for non-holonomic mobile robots. In Proc. IEEE Conf. Intell. Robots Syst 1994; 2: 1133-1140.
Pissard GR. and Rives P. Applying visual servoing techniques to control a mobile hand-eye system. In Proc. IEEE Int Conf Robot Autom1995; 166-171.
Conticelli F, Allotta B, and Khosla PK. Image-based visual servoing of nonholonomic mobile robots. In Proc 38th IEEE Conf Decision Control 1999; 3496-3501.
Burschka D and Hager G. Vision-based control of mobile robots. In Proc IEEE Int Conf Robot Autom 2001; 1707-1713.
Masutani Y, Mikawa M, Maru N, and Miyazaki F. Visual servoing for non-holonomic mobile robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems 1994; 1133-1140.
Tsakiris D, Rives P, and Samson C. Extending visual servoing techniques to nonholonomic mobile robots. In Lecture Notes in Control and Informations Systems. The Confluence of Vision and Control 1998; 237:106-117. http://dx.doi.org/10.1007/BFb0109666
Andreff N, Espiau B. and Horaud R. Visual servoing from lines. The International Journal of Robotics Research 2002; 21(8): 679-699. http://dx.doi.org/10.1177/027836402761412430
Chaumette F. Potential problems of stability and convergence in image-based and position-based visual servoing. In Lecture Notes in Control and Informations Systems. The Confluence of Vision and Control 1998; 237: 66-78.
Hartley R and Zisserman A. Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge, 2000.
Rives P. Visual servoing based on epipolar geometry. In IEEE/RSJ International Conference on Intelligent Robots and Systems 2000; 1: 602-607.
Mariottini GL, Prattichizzo D, and Oriolo G. Epipole-based visual servoing for nonholonomic mobile robots. In IEEE International Conference on Robotics and Automation 2004; 497-503. http://dx.doi.org/10.1109/TRO.2006.886842
Lopez-Nicolas G, Sagues C, Guerrero JJ, Kragic D, and Jensfelt P. Nonholonomic epipolar visual servoing. In IEEE International Conference on Robotics and Automation 2006; 2378-2384.
Mariottini GL, Oriolo G, and Prattichizzo D. Image-based visual servoing for nonholonomic mobile robots using epipolar geometry. IEEE Transactions on Robotics 2007; 23(1): 87-100.
Benhimane S, Malis E, Rives P, and Azinheira JR. Visionbased Control for Car Platooning using Homography Decomposition. IEEE Int Conference on Robotics and Automation 2005; 2173-2178.
Chen J, Dixon WE, Dawson DM, Mcintyre M. Homographybased visual servo tracking control of a wheeled mobile robot. IEEE Transactions on Robotics 2006; 22(2): 406-415. http://dx.doi.org/10.1109/TRO.2006.862476
Fang Y, Dixon WE, Dawson DM, Chawda P. Homography based visual servo regulation of mobile robots. IEEE Trans Syst Man Cybern - Part B: Cybern 2005; 35(5): 1041-1050. http://dx.doi.org/10.1109/TSMCB.2005.850155
Lopez-Nicolas G, Sagues C and Guerrero JJ. HomographyBased Visual Control of Nonholonomic Vehicles. IEEE Int. Conference on Robotics and Automation 2007; 1703-1708.
Boufama B and Mohr R. Epipole and fundamental matrix estimation using virtual parallax. Proc. IEEE Int. Conf Computer Vision 1995; 1030-1036. http://dx.doi.org/10.1109/ICCV.1995.466821
Malis E, Chaumette F. 2 1/2 D Visual Servoing with Respect to Unknown Objects Through a New Estimation Scheme of Camera Displacement. Int J Comput Vision 2000; 37(1): 79- 97. http://dx.doi.org/10.1023/A:1008181530296
Becerra HM, López-Nicolás G, Sagüés C. A Sliding Mode Control Law for Mobile Robots based on Epipolar Visual Servoing from Three Views. IEEE Transactions on Robotics 2011; 27(1): 175-183. http://dx.doi.org/10.1109/TRO.2010.2091750
Faugeras O, Lustman F. Motion and Structure from motion in a piecewise planar environment. International Journal of Pattern Recognition and Artificial Intelligence 1988; 2(3): 485-508. http://dx.doi.org/10.1142/S0218001488000285
Adiv G. Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects. IEEE Trans. Pattern Analysis and Machine Intelligence 1985; 7(4): 384-401. http://dx.doi.org/10.1109/TPAMI.1985.4767678
Daniilidis K, Nagel HH. The Coupling of Rotation and Translation in Motion Estimation of Planar Surfaces. IEEE Conf. Computer Vision and Pattern Recognition 1993; 188- 193. http://dx.doi.org/10.1109/CVPR.1993.340990
Lawton DT and Rieger JH. The Use of Difference Fields in Processing Sensor Motion. ARPA IU Workshop 1983; 78-83.
Irani M, Rousso B, Peleg S. Recovery of Ego-Motion Using Region Alignment. IEEE Transactions on Pattern Analysis and Machine Intelligence 1997; 19(3): 268-272. http://dx.doi.org/10.1109/34.584105
Stein GP, Mano O, Shashua A. A robust method for computing vehicle ego-motion. Proceedings of the IEEE Intelligent Vehicles Symposium 2000, IV2000; 362-368.
Wang ZL, Cai BG, Yi FZ, Li M. Reviews on planar region detection for visual navigation of mobile robot under unknown environment. International Conference on Automation and Robotics 2011.
Shi J, Tomasi C. Good features to track. Proc. IEEE Conf. Computer Vision and Pattern Recognition 1994; 593-600.
Tomasi C, Kanade T. Detection and tracking of point features. Technical report. Carnegie Mellon University 1991.
Negahdaripour S, Prados R, Garcia R. Planar homography: accuracy analysis and applications. IEEE International Conference on Image Processing 2005. ICIP 2005; 1:1089- 1092.
Adiv G. Inherent Ambiguities in Recovering 3D Motion and Structure from a Noisy Flow Field. IEEE Trans. Pattern Analysis and Machine Intelligence 1989; 11:477-489. http://dx.doi.org/10.1109/34.24780