Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

Sankarasrinivasan Seshadri1 , Balasubramanian Esakki This email address is being protected from spambots. You need JavaScript enabled to view it.1, Lung-Jieh Yang2 , Udayagiri Chandrasekhar1 and Sarasu Packiriswamy1

1Centre for Autonomous System Research, Vel Tech University, Chennai, India
2Department of Mechanical and Electromechanical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.


 

Received: August 24, 2015
Accepted: September 15, 2015
Publication Date: December 1, 2015

Download Citation: ||https://doi.org/ 10.6180/jase.2015.18.4.03  


ABSTRACT


This paper presents a novel protocol for vision based flight control of flapping wing micro aerial vehicles (FWMAV). The crux of the work intends to use real time video signals from an on-board camera to control the FWMAVs without using any electronic sensor modules and manual remote control system. A unique control interface is framed for indoor surveillance tasks wherein the user will command the vehicle by providing set of vision information to activate certain flight movements. The control interface is programmed through MATLAB which offers user friendly graphical options to perform vision controlled tasks. Initial simulation is carried out to control the FWMAVs through interfacing MATLAB and Proteus software. The simulation test includes controlling the flapping frequency, directivity of the FWMAV and also validating the vision based systems. In addition, the real time experimentation is performed to control the FWMAV through color based signalling. The obtained results accentuate the usefulness of the developed protocol in controlling of FWMAVs with reprogrammable control interface and light-weight camera that with consequential positive impact on vehicle performance.


Keywords: Color Detection, FWMAVs, GUI, Transmitter Circuitry, Vision System


REFERENCES


  1. [1] Deng, X., Schenato, L. and Sastry, S. S., “Flapping Flight for Biomimetic Robotic Insects: Part II-flight Control Design,” IEEE Transactions on Robotics, Vol. 22, No. 4, pp. 789803 (2006). doi: 10.1109/TRO. 2006.875483
  2. [2] Khan, Z. A. and Agrawal, S. K., “Design and Optimization of a Biologically Inspired Flapping Mechanism for Flapping Wing Micro Air Vehicles,” IEEE International Conference on Robotics and Automation, Rome, Italy, pp. 373378 (2007). doi: 10.1109/ROBOT.2007. 363815
  3. [3] Shigeoka, K. S., “Velocity and Altitude Control of an Ornithopter Micro Aerial Vehicle,” Master’s thesis, The University of Utah, USA (2007).
  4. [4] Yang, L. J., Balasubramanian, E., Chandrasekhar, U., Hung, K.-H. and Cheng, C.-M., “Practical Flapping Mechanisms for 20 cm-span Micro Air Vehicles,” International Journal of Micro Aerial Vehicle, Vol. 7, No. 2, pp. 181202 (2015). doi: 10.1260/1756-8293.7. 2.181
  5. [5] de Croon, G., de Clerq, K., Ruijsink, R., Remes, B. and de Wagter, C., “Design, Aerodynamics and Visionbased Control of the DelFly,” International Journal of Micro Air Vehicles, Vol. 1, No. 2, pp. 7197 (2009). doi: 10.1260/175682909789498288
  6. [6] Mak, L. C., Whitty, M. and Furukawa, T., “A Localisation System for an Indoor Rotary-wing MAV Using Blade Mounted LEDs,” Sensor Review, Vol. 28, No. 2, pp. 125131 (2008). doi: 10.1108/02602280810856688
  7. [7] Rudol, P., Wzorek, M., Conte, G. and Doherty, P., “Micro Unmanned Aerial Vehicle Visual Servoing for Cooperative Indoor Exploration,” Proceedings of the 2008 IEEE Aerospace Conference, Montana, USA, pp. 110 (2008). doi: 10.1109/AERO.2008.4526558
  8. [8] Kemp, C., Visual Control of a Quad-Rotor Helicopter, Ph.D. Dissertation, Churchill College, University of Cambridge, UK (2006).
  9. [9] Elik, K. C., Chung, S.-J. and Somani, A., “Mono-vision Corner SLAM for Indoor Navigation,” IEEE International Conference on Electro/Information Tech - nology 2008, Ames, IA, pp. 343348 (2008). doi: 10. 1109/EIT.2008.4554326
  10. [10] Ahrens, S., Vision-based Guidance and Control of a Hovering Vehicle in Unknown Environments, M.Sc. thesis, MIT, USA, June (2008). doi: 10.1109/ROBOT. 2009.5152680
  11. [11] Ruffier, F. and Franceschini, N., “Optic Flow Regulation: the Key to Aircraft Automatic Guidance,” Robotics and Autonomous Systems, Vol. 50, No. 4, pp. 177194 (2005). doi: 10.1016/j.robot.2004.09.016
  12. [12] Barrows, G., Neely, C. and Miller, K., “Optic Flow Sensors for MAV Navigation,” in Fixed and Flapping Wing Aerodynamics for Micro Air Vehicle Applications, Progress in Astronautics and Aeronautics, T. J. Mueller, Ed. AIAA, Vol. 195, pp. 557574 (2001). doi: 10.2514/5.9781600866654.0557.0574
  13. [13] Yu, Z.-Y., et al., “3D Vision Based Landing Control of a Small Scale Autonomous Helicopter,” International Journal of Advanced Robotic Systems, Vol. 4, No. 1, pp. 5156 (2007). doi: 10.5772/5710
  14. [14] Sinisa, T. and Nechyba, M. C., “A Vision System for Intelligent Mission Profiles of Micro Air Vehicles,” IEEE Transactions on Vehicular Technology, Vol. 53, No. 6, pp. 17131725 (2004). doi: 10.1109/TVT.2004. 834880
  15. [15] De Christophe, W., et al., “Autonomous Flight of a 20- gram Flapping Wing MAV with a 4-gram Onboard Stereo Vision System,” IEEE International Conference on Robotics and Automation (ICRA 2014), Hong-Kong, pp. 49824987 (2014). doi: 10.1109/ICRA.2014.6907 589
  16. [16] Moore, R. J. D., et al., “Autonomous MAV Guidance with a Lightweight Omnidirectional Vision Sensor,” IEEE International Conference on Robotics and Automation (ICRA 2014) Hong-Kong, pp. 38563861 (2014). doi: 10.1109/ICRA.2014.6907418
  17. [17] Shen, S., Nathan M. and Vijay K., “Autonomous Multifloor Indoor Navigation with a Computationally Constrained MAV,” IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, pp. 2025 (2011). doi: 10.1109/ICRA.2011.5980357
  18. [18] Ruffier, F. and Franceschini, N., “Optic Flow Regulation: the Key to Aircraft Automatic Guidance,” Robotics and Autonomous Systems, Vol. 50, No. 4, pp. 177194 (2005). doi: 10.1016/j.robot.2004.09.016
  19. [19] de Croon, G., de Weerdt, E., de Wagter, C. and Remes, B., “The Appearance Variation Cue for Obstacle Avoidance,” IEEE International Conference on Robotics and Biomimetics (ROBIO), Tianjin, pp. 16061611 (2010). doi: 10.1109/ROBIO.2010.5723570
  20. [20] Baek, S. and Fearing, R., “Flight Forces and Altitude Regulation of 12 Gram I-Bird,” IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Tokyo, Japan, pp. 454460 (2010). doi: 10.1109/BIOROB.2010.5626347
  21. [21] Zufferey, J.-C., Klaptocz, A., Beyeler, A., Nicoud, J.- D. and Floreano, D., “A 10-gram Microflyer for Vision-based Indoor Navigation,” Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 3267 3272 (2006). doi: 10.1109/IROS.2006.282436
  22. [22] Zufferey, J.-C., Beyeler, A. and Floreano, D., Flying Insects and Robots, Edited by Dario Floreano, JeanChristophe Zuffery, Mandyam V. Srinavasan and Charlie Ellington, Springer, Chapter 6, Optic Flow to Steer and Avoid Collision in 3D, pp. 7386 (2009). doi: 10. 1007/978-3-540-89393-6_6
  23. [23] Hsiao, F. Y., Hsu, H. K., Chen, C. L., Yang, L. J. and Shen, J. F., “Using Stereo Vision to Acquire the Flight Information of Flapping-wing MAVs,” Journal of Applied Science and Engineering, Vol. 15, No. 3, pp. 213 226 (2012). doi: 10.6180/jase.2012.15.3.02
  24. [24] Nelson, D. R., et al., “Vector Field Path Following for Miniature Air Vehicles,” IEEE Transactions on Robotics, Vol. 23, No. 3, pp. 519529 (2007). doi: 10.1109/ TRO.2007.898976
  25. [25] Cooper, B., Chen, J. and Saxena, A., “Autonomous MAV Flight in Indoor Environments Using Single Image Perspective Cues,” IEEE International Conference on Robotics and automation (ICRA 2011), Shanghai, pp. 57765783 (2011). doi: 10.1109/ICRA.2011.5980136
  26. [26] Fairchild, M. D., Color Appearance Models, John Wiley & Sons (2013). doi: 10.1002/9781118653128. ch16
  27. [27] Sankarasrinivasan, S, Balasubramanian, E., Hsiao, F. Y. and Yang, L. J., “Robust Target Tracking Algorithm for MAV Navigation System,” IEEE International Conference on Industrial Instrumentation and Control (ICIC 2015), Pune, pp. 269274 (2015). doi: 10.1109/ IIC.2015.7150751
  28. [28] Cheng, H.-D., et al., “Color Image Segmentation: Advances and Prospects,” Pattern Recognition, Vol. 34, No. 12, pp. 22592281 (2001). doi: 10.1016/S0031- 3203(00)00149-7