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Ornithopter Project Publications
Biomimetic Millisystems Lab
Ornithopter Project
Overview
Flapping flight provides the high maneuverability necessary for operation in a partially structured indoor environment.  To achieve robust intelligence for tasks such as search and indoor navigation, the maneuverability of the ornithopter will be combined with a learning approach which makes minimal assumptions about the nature of disturbances and obstacles. This approach will develop optimal control policies for single or multiple vehicles. Based on globally optimal distributed reinforcement learning, we propose to develop algorithms for a set of ornithopters to cooperate in sensing and navigation among unmodelled obstacles such as doors and walls.  Our research will be verified with full three dimensional dynamic simulation, a multi-tethered laboratory test-bed, as well as with actual indoor flying ornithopters.

Collaborators:
Prof. Pieter Abbeel, Computer Science Division, UC Berkeley 

Prof. Robert Dudley, UC Berkeley
Recent Results
Ornithopter Free Flight Compared to Wind Tunnel Data (June 2014)

We compare the flight of an ornithopter using free flight data collected from a Vicon motion capture system, to measured wind tunnel force and moment values. We determined that the wind tunnel underestimates the angle of attack of the equilibrium point observed in free flight by 15 degrees, while the equilibrium velocity has an error of 0.1 m/s between the two sets at an average flight speed of 2 m/s. (ICRA 2014). link


H2Bird H2Bird
Cooperative Control for Window Traversal with an Ornithopter MAV (Mar. 2013)

We demonstrate cooperative target-seeking between a 13 gram ornithopter, and a lightweight ground station using computer vision. The H2Bird features a carbon fiber airframe, tail rotor, and elevator, and carries a 2.8 gram payload. The ground station provides heading estimates to the ornithopter using a real-time motion tracking algorithm. A model accurately predicts the backwards reachable region for flight through narrow passages. Autonomous Agents and Multiagent Systems (AAMAS2013). link movie1 movie2


H2Bird H2Bird
Flight Control for Target Seeking by 13 gram Ornithopter (Sept. 2011)

We demonstrate autonomous flight control of 13 gram ornithopter capable of flying toward a target without any remote assistance. For this demonstration, we have developed a closed-loop attitude regulator for the ornithopter using onboard sensing and computational resources. Movie IROS 2011.
iBird seeking light
BOLT: Bipedal Ornithopter for Locomotion Transitioning (Sept. 2011)

Bolt is a 13 gram ornithopter with legs for mixed-mode locomotion. In running modes, wings provide passive stability. With wing assisted running, BOLT can run at 2.5 m/sec while maintaining ground contact. IROS 2011 . movie

BOLT hybrid robot
Altitude Regulation of iBird (Sept. 2010)

We identify free flight aerodynamic forces at a stable equilibrium point of an ornithopter and compare them with the tethered flight aerodynamic forces. We developed a closed-loop altitude regulation for the ornithopter using an external camera and onboard electronics. The results show that the tethered aerodynamic force measurement of a 12 gram ornithopter with zero induced velocity underestimates the total flight force by 24.8 mN.  Movie (1.1 MB .avi)
Biorob 2010.

iBird hover control
Image Proc 2.2 CPU (August 2010)

Image Proc 2.2 design revision by Stan Baek. Board contains cell phone, gyro, accelerometer, 802.15.4 radio, and 2 channel motor driver in 1.4 grams.
Image Proc 2.2
iBird-bot (2010)
Commercially available iBird hover capable ornithopter equipped with ImageProc dsPIC33 CPU board. Total mass 12 grams.
iBird
Efficient Resonant Drive of Flapping (Oct. 2009)

A model for a battery-driven DC motor driving a crank is developed, which shows in experiment a 30% reduction in required power when driven in resonance.
IROS 2009
flapper test bed
Optical Flow on an Ornithopter (Oct. 2009)

Due to the pitching motion of flapping flight, optical flow has a large superimposed velocity component. This component can be sampled at the wing flapping frequency to recover the underlying signal.
IROS 2009
optical flow with flapping
Vamp-bot (2009)
Commercially available VAMP ornithopter with custom low mass electronics. Total mass is approximately 13 grams, including Bluetooth and cell phone camera.
vamp with custom electronics
ImageProc 1 CPU (2008)

PIC CPU with Omnivision camera, design by Fernando Garcia Bermudez. Schematic ImageProc v1.0
ImageProc1 CPU
 

Publications
Stanley S. Baek, Fernando L. Garcia Bermudez, and Ronald S. Fearing,
``Flight Control for Target Seeking by 13 gram Ornithopter,'' IEEE Int. Conf. Intelligent Robots and Systems, IROS Sept. 2011.

K.C. Peterson and R.S. Fearing, ``Experimental Dynamics of Wing Assisted Running for a Bipedal Ornithopter,'' IEEE Int. Conf. Intelligent Robots and Systems, to appear Sept. 2011.

S. Baek and R.S. Fearing,
``Flight forces and altitude regulation of 12 gram i-Bird, IEEE BioRob, Sept. 2010.

S.S. Baek, K.Y. Ma, R.S. Fearing,
``Efficient Resonant Drive of Flapping Wing Robots''
IEEE Int. Conf. Intelligent Robots and Systems, St. Louis, MO October 2009.

F. Garcia Bermudez and R.S. Fearing,
``Optical Flow on a Flapping Wing Robot,''
IEEE Int. Conf. Intelligent Robots and Systems, St. Louis, MO  October 2009.





Sponsored by NSF:
``Robust Ornithopter Flight: From Engineering Models to Cooperative  Indoor Maneuvers''
NSF Disclaimer: ``This material is based upon work supported by the National Science Foundation under Grant No. 0705429. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).''
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