Hostname: page-component-8448b6f56d-dnltx Total loading time: 0 Render date: 2024-04-25T06:57:25.927Z Has data issue: false hasContentIssue false

Vision-based autonomous hovering for a miniature quad-rotor

Published online by Cambridge University Press:  19 July 2013

J. E. Gomez-Balderas
Affiliation:
GIPSA-Lab, UMR 5216 CNRS, Grenoble, France
S. Salazar*
Affiliation:
UMI LAFMIA 3175 CINVESTAV, Mexico
J. A. Guerrero
Affiliation:
HEUDIASYC UMR 7253 CNRS-UTC, France
R. Lozano
Affiliation:
UMI LAFMIA 3175 CINVESTAV, Mexico HEUDIASYC UMR 7253 CNRS-UTC, France
*
*Corresponding author. E-mail: sergio.salazar.cruz@gmail.com

Summary

In this paper, a vision-based scheme for the autonomous hovering of a miniature quad-rotor is developed. Cameras are used to estimate the position and the translational velocity of the vehicle. The dynamic model of the miniature quad-rotor is developed using the Newton–Euler approach. A nonlinear controller based on a separated saturation control strategy for a miniature quad-rotor is presented. To validate the theoretical results, an embedded control system for the miniature quad-rotor has been developed. Thus, the analytic results are supported by experimental tests. Experimental results have validated the proposed control strategy.

Type
Articles
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Borenstein, J., Everett, H. R., Feng, L. and Wehe, D., “Mobile robot positioning-sensors and techniques,” J. Robot. Syst. 14 (4), 231249 (2007).3.0.CO;2-R>CrossRefGoogle Scholar
2.Al-Helal, H. and Sprinkle, J., “UAV Search: Maximizing Target Acquisition,” 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, Oxford (Mar. 2010) pp. 918.Google Scholar
3.Quigley, M., Goodrich, M. A., Griffiths, S., Eldredge, A. and Beard, R. W., “Target Acquisition, Localization, and Surveillance Using a Fixed-Wing Mini-UAV and Gimbaled Camera,” Proceedings of ICRA 2005, Barcelona, Spain (April 18–22, 2005).Google Scholar
H.-W. Schulz, Buschmann, M., Krüger, L., Winkler, S. and Vörsmann, P., “Towards vision-based autonomous landing for small UAVs: First experimental results of the vision system,” J. Aerosp. Comput. Inf. Commun. 4, 785797 (2007).Google Scholar
5.Yu, Z., Nonami, K., Shin, J. and Celestino, D., “3D vision based landing control of a small scale autonomous helicopter,” Int. J. Adv. Robot. Syst. 4 (1), 5156 (2007).CrossRefGoogle Scholar
6.Wu, H., Sun, D. and Zhou, Z., “Micro air vehicle: Configuration, analysis, fabrication, and test,” IEEE/ASME Trans. Mechatronics 9, 108117 (2004).CrossRefGoogle Scholar
7.Kurdila, A., Nechyba, M., Prazenica, R., Dahmen, W., Binev, P., DeVore, R. and Sharpley, R., “Vision-Based Control of Micro–Air–Vehicles: Progress and Problems in Estimation,” 43rd IEEE Conference on Decision and Control, Atlantis Paradise Island, Bahamas (2004) pp. 16351642.Google Scholar
8.Kemp, C., “Visual Control of a Miniature Quad-Rotor Helicopter,” in Churchill College. Ph.D. Thesis (University of Cambridge, 2006).Google Scholar
9.Conroy, J., Gremillion, G., Ranganathan, B. and Humbert, J. S., “Implementation of widefield integration of optic flow for autonomous quad-rotor navigation,” Auton. Robot. 27, 189198 (2009).CrossRefGoogle Scholar
10.He, Z., Iyer, R.V. and Chandler, P. R., “Vision-Based UAV Flight Control and Obstacle Avoidance,” American Control Conference, Minneapolis, MN (June 2006) pp. 21662170.Google Scholar
11.Mondragon, I. F., Campoy, P., Correo, J. F. and Mejias, L., “Visual Model Feature Tracking For UAV Control,” In: IEEE International Symposium on Intelligent Signal Processing, 2007 (WISP 2007), Alcala de Henares, Spain (Oct. 2007) pp. 16.Google Scholar
12.Duchaine, V., Bouchard, S. and Gosselin, M., “Computationally efficient predictive robot control,” IEEE/ASME Trans. Mechatronics 12 (5), 570578 (2007).CrossRefGoogle Scholar
13.Caballero, F., Merino, L., Ferruz, J. and Ollero, A., “Unmanned aerial vehicle localization based on monocular vision and online mosaicking,” Intell. Robot. Syst. 55 323343 (2009).CrossRefGoogle Scholar
14.Altug, E., Ostrowski, J. P. and Taylor, C. J., “Control of a quad-rotor helicopter using dual camera visual feedback,” Int. J. Robot. Res. 24, 329341 (2005).CrossRefGoogle Scholar
15.Castillo, P., Dzul, A. and Lozano, R., “Realtime stabilization and tracking of a four-rotor mini rotorcraft,” IEEE Trans. Control Syst. Technol. 12, 510516 (2004).CrossRefGoogle Scholar
16.Castillo, P., Lozano, R. and Dzul, A., “Stabilization of a mini rotorcraft with four rotors: Experimental implementation of linear and nonlinear control laws,” IEEE Control Syst. Mag. 25, 4555 (2005).Google Scholar
17.Salazar-Cruz, S., Lozano, R. and Escareno, J., “Stabilization and nonlinear control for a novel trirotor mini-aircraft,” Control Eng. Pract. 17, 886894 (2009).CrossRefGoogle Scholar
18.Romero, H., Salazar, S. and Lozano, R., “Real-time stabilization of an eight-rotor UAV using optical flow,” IEEE Trans. Robot. 25, 809817 (2009).CrossRefGoogle Scholar
19.Stevens, B. L. and Lewis, F. L., Aircraft Control and Simulation (John Wiley and Sons, New Jersey, USA, 2003).Google Scholar
20.Teel, A. R., “Global stabilization and restricted tracking for multiple integrators with bounded controls,” Syst. Control Lett. 18, 165171 (1992).CrossRefGoogle Scholar
21.Stein, D., Scheinerman, E. R. and Chirikjian, G. S., “Mathematical models of binary spherical-motion encoders,” IEEE/ASME Trans. Mechatronics 8 (2), 234244 (2003).CrossRefGoogle Scholar
22.Green, W. E., Oh, P. Y. and Barrows, G. L., “Flying Insect Inspired Vision for Autonomous Aerial Robot Maneuvers in Near-Earth Environments,” Proceedings of IEEE International Conference on Robotics and Automation, New Orleans, LA (2004) pp. 23472352.Google Scholar
23.Zhang, L., Dehghani, A., Zhenwei, S., King, T., Greenwood, B. and Levesley, M., “Development of a mechatronic sorting system for removing contaminants from wool,” IEEE/ASME Trans. Mechatronics 10 (3), 297304 (2005).CrossRefGoogle Scholar
24.Faugeras, O., “Stratification of three-dimensional vision: Projective, affine, and metric representations,” J. Opt. Soc. Am. 12 (3), 465484 (1995).CrossRefGoogle Scholar
25.Bar, L., Sochen, N. and Kiryati, N., “Variational Pairing of Image Segmentation and Blind Restoration,” Proceedings of the ECCV, Prague, Czech Republic, Part II: LNCS 3022 (2004) pp. 166177.Google Scholar
26.Canny, J., “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8 (6), 679698 (1986).CrossRefGoogle ScholarPubMed
27.Murateta, L., Doncieuxa, S., Briereb, Y. and Meyera, J., “A contribution to vision-based autonomous helicopter flight in urban environments,” Robot. Auton. Syst. 50, 195209 (2005).CrossRefGoogle Scholar
28.Stowers, J., Bainbridge-Smith, A., Hayes, M. and Mills, S., “Optical flow for heading estimation of a quad-rotor helicopter,” Int. J. Micro Air Vehicles 1 (4), 229239 (2009).CrossRefGoogle Scholar
29.Beauchemin, S. S. and Barron, J. L., “The computation of optical flow,” ACM Comput. Surv. 27, 433467 (1995).CrossRefGoogle Scholar
30.Bouguet, J. Y., “Pyramidal implementation of the Lucas–Kanade feature tracker,” Intel Corp. Microprocess. Res. Lab., 1–9 (1999).Google Scholar
31.Peuteman, J., Aeyels, D. and Sepulchre, R.. “Boundedness properties for time-varying nonlinear systems,” SIAM J. Control Optim. 39 (5), 14081422 (2000).CrossRefGoogle Scholar
32.Hartley, R. and Zisserman, A., Multiple View Geometry, 2nd ed. (Cambridge University Press, 2003), New York, NY, USA. ISBN: 0521540518.Google Scholar
33.Rabbit Semiconductors, Dynamics C user manual 2007, http://www.rabbitsemiconductor.com/.Google Scholar