A Novel Vision Based Protocol for Controlling Flapping Wing Vehicles in Indoor Surveillance Mission

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.

[1]  Spencer Greg Ahrens.  Vision-based guidance and control of a hovering vehicle in unknown environments , 2008 .

[2]  B. Remes,et al.  Design, Aerodynamics, and Vision-Based Control of the DelFly , 2009 .

[3]  Balasubramanian Esakki,et al.  Practical Flapping Mechanisms for 20 cm-span Micro Air Vehicles , 2015 .

[4]  Ronald S. Fearing,et al.  Flight forces and altitude regulation of 12 gram I-Bird , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[5]  S. Sankarasrinivasan,et al.  Robust target tracking algorithm for MAV navigation system , 2015, 2015 International Conference on Industrial Instrumentation and Control (ICIC).

[6]  Vijay Kumar,et al.  Autonomous multi-floor indoor navigation with a computationally constrained MAV , 2011, 2011 IEEE International Conference on Robotics and Automation.

[7]  Mark D. Fairchild,et al.  Color Appearance Models: Fairchild/Color Appearance Models , 2013 .

[8]  Soon-Jo Chung,et al.  Mono-vision corner SLAM for indoor navigation , 2008, 2008 IEEE International Conference on Electro/Information Technology.

[9]  Ashutosh Saxena,et al.  Autonomous MAV flight in indoor environments using single image perspective cues , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  Thomas J. Mueller,et al.  Optic Flow Sensors for MAV Navigation , 2001 .

[11]  Karthik Dantu,et al.  Autonomous MAV guidance with a lightweight omnidirectional vision sensor , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[12]  Michael C. Nechyba,et al.  A vision system for intelligent mission profiles of micro air vehicles , 2004, IEEE Transactions on Vehicular Technology.

[13]  Kenzo Nonami,et al.  3D Vision Based Landing Control of a Small Scale Autonomous Helicopter , 2007 .

[14]  S. Shankar Sastry,et al.  Flapping flight for biomimetic robotic insects: part II-flight control design , 2006, IEEE Transactions on Robotics.

[15]  Nicolas H. Franceschini,et al.  Optic flow regulation: the key to aircraft automatic guidance , 2005, Robotics Auton. Syst..

[16]  Dario Floreano,et al.  A 10-gram Microflyer for Vision-based Indoor Navigation , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  Timothy W. McLain,et al.  Vector Field Path Following for Miniature Air Vehicles , 2007, IEEE Transactions on Robotics.

[18]  Tomonari Furukawa,et al.  A localisation system for an indoor rotary‐wing MAV using blade mounted LEDs , 2008 .

[19]  G. Conte,et al.  Micro Unmanned Aerial Vehicle Visual Servoing for Cooperative Indoor Exploration , 2008, 2008 IEEE Aerospace Conference.

[20]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..

[21]  Sunil Kumar Agrawal,et al.  Design and Optimization of a Biologically Inspired Flapping Mechanism for Flapping Wing Micro Air Vehicles , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[22]  Guido C. H. E. de Croon,et al.  Autonomous flight of a 20-gram Flapping Wing MAV with a 4-gram onboard stereo vision system , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[23]  H. K. Hsu,et al.  Using Stereo Visionto Acquire the Flight Information of Flapping-Wing MAVs* , 2012 .