A robotic aircraft that follows terrain using a neuromorphic eye

Future Unmanned Air Vehicles (UAV) and Micro Air Vehicles (MAV) will fly in urban areas and very close to obstacles. We have built a miniature (35 cm, 0.840 kg) electrically-powered aircraft which uses a motion-sensing visual system to follow terrain and avoid obstacles. Signals from the 20-photoreceptor onboard eye are processed by 19 custom Elementary Motion Detection (EMD) circuits which are derived from those of the fly. Visual, inertial, and rotor RPM signals from the aircraft are acquired by a flight computer which runs the real-time Linux operating system. Vision-guided trajectories and landings were simulated and automatic terrain-following flights at 2 m/s were demonstrated with the aircraft tethered to a whirling-arm. This UAV project is at the intersection of neurobiology, robotics, and aerospace. It provides technologies for MAV operations.

[1]  Erich Buchner,et al.  Behavioural Analysis of Spatial Vision in Insects , 1984 .

[2]  Svetha Venkatesh,et al.  How honeybees make grazing landings on flat surfaces , 2000, Biological Cybernetics.

[3]  Victor H. L. Cheng,et al.  Technologies for automating rotorcraft nap-of-the-earth flight , 1993 .

[4]  Karl Georg Götz,et al.  Die optischen Übertragungseigenschaften der Komplexaugen von Drosophila , 1965, Kybernetik.

[5]  J. Gibson,et al.  Parallax and perspective during aircraft landings. , 1955, The American journal of psychology.

[6]  R Hengstenberg,et al.  Dendritic structure and receptive-field organization of optic flow processing interneurons in the fly. , 1998, Journal of neurophysiology.

[7]  Alexa Riehle,et al.  Directionally Selective Motion Detection by Insect Neurons , 1989 .

[8]  James S. Albus,et al.  Motion, depth, and image flow , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[9]  John David Anderson,et al.  A History of Aerodynamics , 1997 .

[10]  Jerry M. Mendel,et al.  IEEE control systems society , 2004, IEEE Control Systems.

[11]  Takeo Kanade,et al.  Precision 3-D Modeling for Autonomous Helicopter Flight , 2000 .

[12]  M. Srinivasan,et al.  Motion cues provide the bee's visual world with a third dimension , 1988, Nature.

[13]  Stephen J. Morris,et al.  DESIGN AND FLIGHT TEST RESULTS FOR MICRO-SIZED FIXED-WING AND VTOL AIRCRAFT , 2003 .

[14]  Darrol Stinton The design of the aeroplane , 1983 .

[15]  Raymond W. Prouty,et al.  Helicopter performance, stability, and control , 1986 .

[16]  Nicolas H. Franceschini,et al.  Neuromorphic optical flow sensing for Nap-of-the-Earth flight , 1999, Optics East.

[17]  D. I. Jones,et al.  Obstacle avoidance during aerial inspection of power lines , 2001 .

[18]  W P Chan,et al.  Visual input to the efferent control system of a fly's "gyroscope". , 1998, Science.

[19]  Christopher E. Neely,et al.  Mixed-mode VLSI optic flow sensors for in-flight control of a micro air vehicle , 2000, SPIE Optics + Photonics.

[20]  R. A. Roberts,et al.  The UTA autonomous aerial vehicle-automatic control , 1992, Proceedings of the IEEE 1992 National Aerospace and Electronics Conference@m_NAECON 1992.

[21]  Benjamin Gal-Or Vectored Aircraft and Supermaneuverability , 1990 .

[22]  Heinrich H. Bülthoff,et al.  Insect Inspired Visual Control of Translatory Flight , 2001, ECAL.

[23]  Allan W. Snyder,et al.  Acuity of compound eyes: Physical limitations and design , 2004, Journal of comparative physiology.

[24]  Fabrizio Mura,et al.  Visual control of altitude and speed in a flying agent , 1994 .

[25]  Fumiya Iida,et al.  Goal-Directed Navigation of an Autonomous Flying Robot Using Biologically Inspired Cheap Vision , 2001 .

[26]  Fumiya Iida,et al.  Navigation in an autonomous flying robot by using a biologically inspired visual odometer , 2000, SPIE Optics East.

[27]  N. Franceschini,et al.  From insect vision to robot vision , 1992 .

[28]  Richard M. Murray,et al.  An experimental comparison of controllers for a vectored thrust, ducted fan engine , 1995, Proceedings of 1995 American Control Conference - ACC'95.