Cricket Lab School of Informatics
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Biomorphic wind sensing

Integrating MEMS and aVLSI into robotics

This EPSRC funded project combines microelectromechanical systems (MEMS), analogue very large scale integration electronic circuit design (aVLSI), and neural simulation for controlling robots to develop a wind-sensing system based on insect hair cells. It will be implemented in a fully integrated MEMS/aVLSI chip and interfaced to a robot to test in controlling behaviours such as course stabilisation and upwind flight. Important issues to be addressed include: the most effective mechanical designs and the optimal sensor layouts for the task; the use of short-term synaptic plasticity in hardware neural circuits as a means of adaptive preprocessing of MEMS sensor output; development of hardware and software interfaces between aVLSI chips and digital circuits and neural simulations; and the design of insect inspired neural controllers for combining different sensory inputs and responding robustly in complex environments such as turbulent windflow.


Principal Investigator: Barbara Webb
Co-Investigators: Rebecca Cheung, Alister Hamilton, Tom Stevenson
Recognised Researcher: Richard Reeve
Research Fellow: Yaxiong Zhang
Research Associate: Petros Argyrakis
PhD student: Theophile Gonos


Barbara Webb

Institute of Perception, Action and Behaviour
JCMB, King's Buildings
Mayfield Rd
Edinburgh EH9 3JZ

Room: JCMB 1107     Phone: 0131 651 3453



Chapman, T. and Webb, B. A neuromorphic hair sensor model of wind-mediated escape in the cricket International Journal of Neural Systems (1999), 9(5):397-403

Argyrakis, P. Hamilton, A. Webb, B. Zhang, Y. Gonos, T. and Cheung, R. Fabrication and characterization of a wind sensor for integration with neuron circuit Microelectronic Engineering 84 (2007), 1749-1753

Zhang, Y. Hamilton, A. Cheung, R Webb, B. Argyrakis, P and Gonos, T. Integration of Wind Sensors and Analogue VLSI fir an Insect-Inspired Robot IWANN 2007, LNCS 4507, pp. 438-446 (2007)

Gonos, T. and Webb, B. Using Homeostatic Neurons for Sensor Self-Calibration to be presented at the Biological Approaches for Engineering Conference (2008)

Internal information

Internal information for research group.