Part II Workshop Hardware - Capabilities and Resources Dr. Anita Flynn

Prof. Kristofer S.J. Pister’s teamBerkeley Sensor and Actuator Center

University of California, Berkeley

Prof. Kristofer S.J. Pister’s teamBerkeley Sensor and Actuator Center

University of California, Berkeley

Part IIWorkshop Hardware - Capabilities and Resources

Dr. Anita Flynn

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Building on 20 Years of Sensor Research

• MEMS devices, sensors & microrobots since ’80s

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Building on 20 Years of Sensor Research

• Autonomous robots since ‘87

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Building on 20 Years of Sensor Research

• RF sensor network comms since ‘99

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Building on 20 Years of Sensor Research

• Recently: comms standards (IEEE802.15.4e)– Latest: Reference implementation for full stack (Watteyne)

• Open-source hardware & software in your kit• Standards help industries grow• Reference implementations help people port apps• This workshop: networking your sensors

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Outline

• Wireless Sensor Networks• Workshop Hardware• Applications

wsn.eecs.berkeley.edu

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Outline

• Wireless Sensor Networks• Workshop Hardware• Applications

wsn.eecs.berkeley.edu

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Wireless Sensor Networks

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S. Oh et al, "Tracking and coordination of multiple agents using sensor networks: system design, algorithms and experiments," Proc. of the IEEE, 2007.S. Kim et al, “Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks,” IPSN, Cambridge, MA, April 2007A. Ledezci, http://www.isis.vanderbilt.edu/projects/countersniperJ. Lees et al, “Reventador Volcano 2005: Eruptive Activity Inferred from Seismo-Acoustic Observation”, Jnl, of of Volcanology and Geothermal Research, 2007

Wireless Sensor Networks

Sensor Networks for SecurityStructural Monitoring

Sniper Localization Environmental Monitoring

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Building Automation

Smart Grid Applications

IndustrialAutomation

Wireless Sensor Networks

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Outline

• Wireless Sensor Networks• Workshop Hardware• Applications

wsn.eecs.berkeley.edu

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Wireless Motes

• Pister Group: numerous wireless sensor boards– Called them motes (short for “dust motes)– Used for various sensor research projects– Used for software development of protocol stacks– The latest: variety of 3-axis inertial sensors– Used in this workshop to demo OpenWSN stack– But OpenWSN can be ported to any processor

wsn.eecs.berkeley.edu

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The General Inertial Navigation Assistant (GINA)

• Wireless mote with:– Two 3-axis accels– 3-axis gyroscope– 3-axis compass– 802.15.4 radio– 16-bit processor– Expansion headers

GINA 1January 2008

GINA 2.0March 2009

GINA 2.1July 2009

GINA 2.2June 2010

http://warpwing.sourceforge.net/

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What’s In Your Kit?

• Open-source HW/SW• Board layout files available online• OpenWSN reference implementation, GPL-license (?)• http://warpwing.sf.net• http://wsn.eecs.berkeley.edu/workshop

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Sensitivity

• One 3-axis accelerometer for high rate (+- 8 G)• coarse sensitivity• noise density of 750 mG/rtHz, bandwidth set to 1.8 kHz• -> min resolvable acceleration: 32 mG

• Another 3-axis accelerometer for low rate (+- 2 G)• but higher sensitivity• noise density of 50 mG/rtHz, bandwidth set to 40 Hz• -> min resolvable acceleration: 0.32 mG

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Primary Design Considerations

• Low mass -> targeted for flying vehicles

• Plenty of actuator outputs

• Low power• Low cost components• Ease or low cost of manufacturing

Not:

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Power Consumption

TX+g

yro+m

ag+xl

+adc

TX+g

yro+xl

+adc

TX+xl

+adc

TX+a

dc

radio tx

radio id

le

radio sle

epLP

M3

90.979.8

55.8 54.9 54.3

7.4 4.2 1.5

GINA 2.2b/c Power Consumption

AveragePower (mW)

16 MHz clock, 3 ms instrumentation loop

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Outline

• Wireless Sensor Networks• Workshop Hardware• Applications

wsn.eecs.berkeley.edu

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Mini-Rocketry

• Put a 10 g micro satellite into low-earth orbit

• With a guidable rocket with cheap, off-the-shelf components

• To deploy a wireless sensor network

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Motion Capture

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Application to Mini-Robotics

Coaxial Helicopter(UCB)

Rotochure(GATech)

Quadrotor(UMD)

Crawler(UCB)

Coaxial Helicopter(GATech)

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Gas/Water Flow Monitoring

• GINA board attached to stove’s flexible gas tubing

• X-axis acceleration is monitored at 300 Hz

26RespirationHeart Rate

Basic Health Monitoring

Acceleration data Collected from a GINA mote strapped onto the chest

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Footstep Localization

d2

k(t)k(t+τ1)

k(t+ τ2)

d1

sensor node

vibration source

Waveform of a typical footstep

Equivalent spectrum

• Where is someone walking?• Use the time difference of arrival of

the seismic wave generated by a footstep