Initial experiments of reconfigurable sensor adapted by evolution
In this paper we describe the initial development of efficient mechanisms for smart sensing which will lead to higher quality data.
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In this paper we describe the initial development of efficient mechanisms for smart sensing which will lead to higher quality data.
Outer solar system exploration and missions to comets and planets with severe environmental conditions require long-term survivability of space systems. This challenge has recently been approached with new ideas, such as using mechanisms for hardware adaptation inspired from biology.
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This article focuses on the properties of a fine grained reconfigurable transistor array currently under test at the Jet Propulsion Laboratory (JPL).
This paper introduces a third approach to Evolvable Hardware (EHW) called mixtrinsic EHW (MEHW).
This paper describes the design of a reconfigurable chip programmable at the transistor level and oriented to the implementation of Evolvable Hardware (EHW) experiements.
Evolvable Hardware (EHW) refers to HW design and self-reconfiguration using evolutionary/genetic mechanisms. The paper presents an overview of some key concepts of EHW, describing also a set of selected applications.
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In this paper we describe the initial development of efficient mechanisms for smart on-board adaptive sensing, adaptively controlling the reconfigurable pre-processing analog electronics using evolvable hardware, which will lead to higher quality, lean data.
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The chapter is concerned with the design of planar dielectric layer diffraction gratings, which exhibit sharp resonances due to the coupling of exterior evanescent diffractive fields to the leaky modes of dielectric waveguides.
The paper introduces an approach to automated synthesis of CMOS circuits, based on evolution on a Programmable Transistor Array (PTA).
The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of measurement, analytical and communication systems.
We investigate the evolutionary dynamics of a finite population of sequences adapting to NK fitness landscapes.
Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.
Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.
We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation. We also report on the development of a hardware platform for integrated tuning and closed loop operation of MEMS gyroscopes. The control of this device is implemented through a digital design on a Field Programmable Gate Array (FPGA). The hardware platform easily transitions to an embedded solution that allows for the miniaturization of the system to a single chip.