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