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.
People
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
Contact
Barbara Webb
Institute
of Perception, Action and Behaviour
JCMB, King's Buildings
Mayfield Rd
Edinburgh EH9 3JZ
Room: JCMB 1107 Phone: 0131 651 3453
Email: bwebb@inf.ed.ac.uk
Publications
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.