Biomimetic Underwater Robot Program
We are developing neurotechnology based on the neurophysiology and behavior of animal models. We developed two classes of biomimetic autonomous underwater vehicles (see above). The first is an 8-legged ambulatory vehicle that is based on the lobster and is intended for autonomous remote-sensing operations in rivers and/or the littoral zone ocean bottom with robust adaptations to irregular bottom contours, current and surge. The second vehicle is an undulatory system that is based on the lamprey and is intended for remote sensing operations in the water column with robust depth/altitude control and high maneuverability.
These vehicles are based on a common biomimetic control, actuator and sensor architecture that features highly modularized components and low cost per vehicle. Operating in concert, they can conduct autonomous investigation of both the bottom and water column of the littoral zone or rivers. These systems represent a new class of autonomous underwater vehicles that may be adapted
to operations in a variety of habitat
We are collaborating with investigators at The University of California, The University of Alabama and Newcastle University to apply principles of synthetic biology to the integration of a hybrid microbot. The aim of this research is to construct Cyberplasm, a micro-scale robot integrating microelectronics with cells in which sensor and actuator genes have been inserted and expressed. This will be accomplished using a combination of cellular device integration, advanced microelectronics and biomimicry; an approach that mimics animal models; in the latter we will imitate some of the behavior of the marine animal the sea lamprey. Synthetic muscle will generate undulatory movements to propel the robot through the water. Synthetic sensors derived from yeast cells will be reporting signals from the immediate environment. These signals will be processed by an electronic nervous system. The electronic brain will, in turn, generate signals to drive the muscle cells that will use glucose for energy. All electronic components will be powered by a microbial fuel cell integrated into the robot body.
This research aims to harness the power of synthetic biology at the cellular level by integrating specific gene
into bacteria, yeast and mammalian cells to carry out device like functions. Moreover this approach will allow the cells/bacteria to be
so that the input/output (I/O) requirements of device integration can be addressed. In particular we plan to use visual receptors to couple electronics to both sensation and actuation through light signals. In addition synthetic biology will be carried out at the systems level by interfacing multiple cellular /bacterial devices together, connecting to an electronic brain and in effect creating a multi-cellular biohybrid micro-robot. Motile function will be achieved by engineering muscle cells to have the minimal cellular machinery required for excitation/contraction coupling and contractile function. The muscle will be powered by mitochondrial conversion of glucose to ATP, an energetic currency in biological cells, hence combining power generation with actuation.
We are collaborating with investigators at Harvard University School of Engineering and Applied Sciences, the Wyss Institute for Biologically Inspired Engineering and CentEye to develop colonies of Robotic Bees. This project integrates approaches at the body, brain and colony level. Inspired by the biology of a bee and the insectÕs hive behavior, we aim to push advances in miniature robotics and the design of compact high-energy power sources; spur innovations in ultra-low-power computing and electronic
sensors; and refine coordination algorithms to manage multiple, independent machines
Electronic Nervous Systems
We are also developing neuronal circuit based controllers for both robots and neurorehabilitative devices. These controllers are based on
Al Selverston, Marine Science Center
Jan Witting, Sea Education Associates
Matt Sullivan, Schlumberger
Anthony Westphal, Northeastern University
Clint Valentine, Northeastern University
Dan Blustein, Kalamazoo College
Steve Smith, SUNY Stony Brook
Lara Lewis, Bucknell University
Lin Zhu, Nanjing University
Ryan Myers, Northeastern University
Matt Perry, University of Rhode Island
Neurotechnology for Biomimetic Robots
Biomechanisms of Swimming and Flying
Quicktime VR View of the Ayers Robotics Laboratory
On Line Animations of Biomimetic Systems
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IEEE Proc. on Intelligent Robots and Systems 1: 574-581
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Systems Institute, Portsmouth, N.H., Pp. 60-68
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- Ayers, J., Witting, J., McGruer, N., Olcott, C., Massa, D. (2000) Lobster Robots. In: Proceedings of the International Symposium on Aqua Biomechanisms. T. Wu and N, Kato, [eds]. Tokai University.
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- McGruer, N., T. Truong, T. Barnes, X. Lu, and J. Aceros (2001)
Biomimetic Flow And Contact/Bending MEMs Sensors. In: Neurotechnology for Biomimetic Robots,. J. Ayers, J. Davis and A. Rudolph [eds]. MIT Press
- Witting, J. and K. Safak(2001) SMA Actuators Applied To Biomimetic Underwater Robots
In: Neurotechnology for Biomimetic Robots,. J. Ayers, J. Davis and A. Rudolph [eds]. MIT Press.
- Wilbur, C., W. Vorus, Y. Cao and S. Currie (2001) A Lamprey-Based Undulatory Vehicle. In: Neurotechnology for Biomimetic Robots,. J. Ayers, J. Davis and A. Rudolph [eds]. MIT Press.
- Ayers, J. , A. Volkovski, N. Rukov, A. Selverston, & H.D.I. Abarbanel, M. R. 2003 Building a Brain for the Lobster Robot Using Electronic Neurons. In International Conference on Non-Linear Wave Physics, pp. 3 Nizhny-Novgorad, Russia.
- Ayers, J. (2004). Architectures for Adaptive Behavior in Biomimetic Underwater Robots. Bio-mechanisms of Swimming and Flying. N. Kato, Ayers, J., Morikawa, H. Tokyo, Springer-Verlag: 171-187.
- Lee, Y. J., J. Lee., Y.B. Kim, J. Ayers , A. Volkovskii , A. Selverston , H. Abarbanel , M. Rabinovich (2004). "Low Power Real Time Electronic Neuron VLSI Design Using Subthreshold Techniques,." IEEE Circuits and Systems 4: 744-747.
- Ayers, J. (2004) Underwater Walking. Arthropod Structure and Development 33, 347-360.
- Selverston, A. I., Rabinovich, M. I., Huerta, R., Novotny, T., Levi, R., Arshavsky, Y., Volkovskii, A., Ayers, J. & Pinto, R. (2005) Biomimetic Central Pattern Generators for Robotics and Prosthetics. In ROBIO2004, IEEE International Conference on Robotics and Biomimetics, 1: 885 - 888. Shenyang, China.
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- Selverston, A. & Ayers, J. (2006) Oscillations and Oscillatory Behavior in Small Neural Circuits. Biological Cybernetics 95:537Š554
- Ayers, J. and Witting, J. (2007) Biomimetic Approaches to the Control of Underwater Walking Machines. Philosophical Transactions of the Royal Society, A, 365, 273Š295
- Lee, Y.. Lee, J. Kim, Y.B., Ayers, J. (2005). Low power CMOS adaptive electronic central pattern generator design. IEEE Circuits and Systems 2: 1350-1353
- J. Lee, Y. J. Lee, K. Kim, Y. B. Kim, and J. Ayers (2007) "Low Power CMOS Adaptive Electronic Central Pattern Generator Design for a Biomimetic Robot," Neurocomputing 71: 284-296.
- Ayers, J. and N. Rulkov (2007). Controlling Biomimetic Underwater Robots with Electronic Nervous Systems. In: Bio-mechanisms of Animals in Swimming and Flying. N. Kato and S. Kamimura. Tokyo, Springer-Verlag. Pp. 295-306.
- Ayers, J., Rulkov, N., Knudsen, D., Kim, Y-B., Volkovskii, A. Selverston, A.(2010). "Controlling Underwater Robots with Electronic Nervous Systems." Applied Bionics and Biomechanics 7: 57-67.
- Blustein, D. and J. Ayers, (2010) A conserved network for control of arthropod exteroceptive optical flow reflexes during locomotion. Lecture Notes in Artificial Intelligence, 6226: 72-81
- Hu, J., YB. Kim, J. Ayers (2010) A Low Power 100M½ CMOS Front-End Transimpedance Amplifier for Biosensing Applications IEEE Circuits and Systems. 53: 541 - 544
- Westphal, A., Rulkov, N., Ayers, J., Brady, D., & Hunt, M. 2011. Controlling a lamprey-based robot with an electronic nervous system. Smart Structures and Systems. 7(6): 471 - 484
- .Ayers, J, Westphal, A. & Blustein, D. (2011) A Conserved Neural Circuit-Based Architecture for Ambulatory and Undulatory Biomimetic Robots. Marine Technology Society Journal 45(4): 147-152.
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