S.N.A.K.E.: A Dynamically Reconfigurable Artificial Sensate Skin ...

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flag 0x80 indicates a successful write to flash. As previously noted, the Bootloader will wait indefinitely for an instruction, but it could be easily changed to start execution of a program after a determined amount of time. Once execution starts though, the bootloader can’t be invoked again unless a reset is generated (hardware or software initiated) or the application code explicitly includes a mean to invoke it. This can be easily accomplished by generating either a Watchdog timer timeout or an invalid write to its counter register. 4.1.2 Sampling Code The second large firmware component is the application code that deals with sensor sampling. This is probably, the principal software component, given that it is mainly where theDynamically Reconfigurable feature of the Skin Patches lies 4 . As the reader may recall, one of the main goals of the project is to demonstrate that the amount of required band- width and other resources can be minimized if each node is given processing power. By doing this, the need to route pixelated data to a centralized processing unit is practically eliminated. Although this code could be used if the Skin Patches are used as data extraction devices, it is mainly intended for the case when the Skin Patches are being used as stand-alone devices. Its main purpose is to set the rate at which the sensors are sampled, process the generated data, calculate higher order features and possibly transfer these to a PC through a Brain if further processing is needed. Concurrent sampling and processing is possible because the sampling and timing of the application is carried out by the microcontroller peripherals, so the processor core is left free to process the generated data. This is shown in Figure 4-3. Lets now describe what the microcontroller does after starting up. After a reset, the application configures the clocking unit to run at 8.000 Mhz, initializes the I 2 C module as a slave device and designates an ADC memory channel for each one of the sensor modes 5 . 4 The other one being its ability to be reprogrammed 5 The MSP430 ADC module is equipped with 10 sampling channels each one of them with a 16-bit conversion result register 86
Figure 4-3: Sampling timing example Then, the Timer B peripheral is configured to generate 6 different timing intervals which trigger the sensor sampling events. With this approach, each sensor can be sampled at a different rate according to its needs. Once a sensing event is generated, its associated sensor is sampled and the result is stored in its assigned memory register. Depending on the sensor type, some additional tasks are sometimes performed before their information is stored, and higher-order features can be then calculated. Sensors that need additional tasks are mentioned in the following list: Pressure sensing: since there are four pressure sensors controlled by a multiplexer, every time a sampling event is generated (120Hz), the multiplexer address is changed, and a different sensor is sampled. This effectively reduces the sampling rate of each one of the four pressure sensors to 30Hz. After sensing, pressure samples are downsampled to 8-bits, and stored in a 4-byte array, one for every sensor. Sound sensing: sound is the only sensor which is not downsampled for signal fidelity reasons. It is also the sensor with the fastest sampling rate (8Khz). The result of the samples is stored in a 1Kb circular array that uses 2 bytes per sample. Strain/Bending: strain gages are gated through a MOSFET transistor so that the Wheat- stone bridge used for both strain gages doesn’t waste energy when not in use. When a sampling event is generated for either one of the strain gages, they are first turned on, 87
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Author S.N.A.K.E.: A Dynamically Re
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S.N.A.K.E.: A Dynamically Reconfigu
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Table of Contents Abstract 3 Acknow
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List of Figures 2-1 Created by MIT
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E-1 OpenGL Control Header File . .
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Chapter 1 Introduction “Imaginati
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The current project, named S.N.A.K.
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Hardware Each Skin Patch is compose
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living tissue. Particularly in the
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Figure 2-2: Leonardo’s Hand great
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Artificial Sensate Skins elsewhere
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2.1.2 Ultra-dense Sensor Arrays Thi
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2.2 Flexible Circuits Although, not
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2.2.2 Other Technologies Figure 2-6
Page 36 and 37: human skin. The following design pr
Page 38 and 39: (a) Skin Patches as data extraction
Page 40 and 41: Figure 3-3: I 2 C Routing pattern T
Page 42 and 43: 3.2.2 Peer to Peer As we already me
Page 44 and 45: 5. Audio: by adding a MEMS micropho
Page 46 and 47: Table 3.1: Material thicknesses and
Page 48 and 49: (a) Node Front (b) Node Back Figure
Page 50 and 51: Figure 3-9: Skin Patch mechanical t
Page 52 and 53: used, which only further complicate
Page 54 and 55: 8. Teardrops and filleting were add
Page 56 and 57: (a) 7.4V, 2.2mAh Li-ion Battery (b)
Page 58 and 59: in more detail in the Results Chapt
Page 60 and 61: has a 30mA forward current with a f
Page 62 and 63: Figure 3-14: Strain gage layer prot
Page 64 and 65: an unbalanced Wheatstone bridge, fr
Page 66 and 67: Figure 3-16: QTC response curve for
Page 68 and 69: (a) Prototype boards used to calibr
Page 70 and 71: whisker is epoxied to the package o
Page 72 and 73: Sound The only sensing modality add
Page 74 and 75: Figure 3-20: Brain regular PCB fabr
Page 76 and 77: 3.4.3 Communications unit The Commu
Page 79 and 80: Chapter 4 Software “A Scientist d
Page 81 and 82: Networks. Why is this relevant? Mai
Page 83 and 84: Figure 4-1: Bootloader memory map C
Page 85: Bit Flag Name Description 0x01 FILE
Page 89 and 90: We also mentioned before that there
Page 91 and 92: Code Instruction Description 0xA0 R
Page 93 and 94: Component Description 1 Indicates t
Page 95 and 96: last chapter. Figure 4-5: Automatic
Page 97 and 98: An important point to stress is tha
Page 99 and 100: (a) Rotation control (b) Zooming co
Page 101 and 102: 4.3 Communications Software The las
Page 103 and 104: 4.3.2 Peer to Peer Peer to peer com
Page 105 and 106: Chapter 5 Analysis of Results and E
Page 107 and 108: Figure 5-1: Stress concentration po
Page 109 and 110: of the assembled skin patch don’t
Page 111 and 112: Node SG1 SG2 R(X) R(Y) Δ(X) Δ(Y)
Page 113 and 114: Or, ∆R = R3 R3 R3 + RC (5.2) Howe
Page 115 and 116: R3 Microstrain 162Ω −99.7337969
Page 117 and 118: Figure 5-3: Strain Gage electronic
Page 119 and 120: (a) Data from both strain gages (b)
Page 121 and 122: (a) Pressure data being extracted f
Page 123 and 124: many of these did not work as expec
Page 125 and 126: Data plots were also extracted for
Page 127 and 128: (a) Temperature sensor data plots (
Page 129 and 130: Figure 5-12: Raw microphone data wi
Page 131 and 132: (a) Activity sensor data (b) Whiske
Page 133 and 134: 5.3 Performance Metrics We have pre
Page 135 and 136: (a) I 2 C data when a 1500Ωs resi
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Component # per node Current consum
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Finally, since power is readily ava
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Chapter 6 Conclusions and Future Wo
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surface can be used to sense pressu
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Implement P2P Communications: curre
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Appendix A Abbreviations and Symbol
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Appendix B Bill of Materials 149
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Appendix C Schematics and PCB Layou
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1 1 2 2 3 3 4 4 D D C C B B A A Tit
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Amp1 P0Amp101 P0Amp102 P0Amp103 P0A
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P0Cin02 P0East06 P0North06 P0South0
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Cain P0C ain01 P0Cain02 L1 P0L101 P
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Figure C-10: Node Bottom Overlay 16
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4 3 2 1 A A Brain Communications Ac
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C3v P0C3v01 P0C3v02 Cavcc P0Cavcc01
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Appendix D Firmware 167
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C:\Documents and Settings\Gerardo\M
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Appendix E PC Code 183
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1 c:\Documents and Settings\Gerardo
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12 c:\Documents and Settings\Gerard
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Bibliography [1] John C. Ansel. Ski
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[33] Joseph Jacobson, B Comiskey, C
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[68] Vilis Tutis. The physiology of
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