COLORADO SCHOOL OF MINES
Robotics, Autonomous Systems, and Control CSM Capabilities
Kevin L. Moore
G.A. Dobelman Distinguished Chair and Professor of Engineering
Director, Center for Automation, Robotics, and Distributed Intelligence
Division of Engineering
Colorado School of Mines
Golden, Colorado
Kevin L. Moore, Colorado School of Mines
Outline
COLORADO SCHOOL OF MINES
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Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
Colorado School
of Mines
COLORADO SCHOOL OF MINES
Located in Golden, Colorado, USA
10 miles West of Denver
CSM sits in the foothills of the Rocky Mountains
CSM has about 300 faculty and 4000 students
CSM is a public research institution devoted to
engineering and applied science, especially:
CARDI
• Discovery and recovery of resources
•14
faculty, interdisciplinary
• Conversion of resources to materials and energy
•Electrical,
Mechanical,
Civil
• Utilization in advanced
processes and
products
• Economic and social systems necessary to ensure
•Computer
Science, Math
prudent and provident use of resources in a
•Bio-medicine,
Bio-mechanics
sustainable global society
Kevin L. Moore, Colorado School of Mines
COLORADO SCHOOL OF MINES
Degrees at CSM
(Grad and Undergrad)
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Degrees pursued by major
Chemistry
Chemical Eng
Economics/Business
Engineering
Environmental Science/Eng
Geochemistry
Geology and Geological Eng
Geophysics and Geophysical Eng
Math/Computer Science
Material Science
Mining and Earth Systems Eng
Metallurgical and Materials Eng
Petroleum Engineering
Physics
Kevin L. Moore, Colorado School of Mines
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CSM Engineering Division
COLORADO SCHOOL OF MINES
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B.S. in Engineering with Specialties in
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M.S/Ph.D. in Engineering Systems
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Civil
Electrical
Environmental
Mechanical
Civil
Electrical
Environmental
Mechanical
Bioengineering and Life Sciences Minor
– Includes biomedical engineering, biophysics
– Pre-Medical & Life Sciences
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5-year Programs (BS+MS)
– Engineering Physics
– Engineering Systems
– Environmental Science
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Humanitarian Engineering Minor
– The application of math, science, and engineering to improve the wellbeing of underserved populations
Kevin L. Moore, Colorado School of Mines
CSM Research (Control-Oriented view)
COLORADO SCHOOL OF MINES
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Materials
– Nuclear
– Welding
Energy
– “Traditional” (e.g., Petroleum Institute)
– Combustion
– Renewable
 Colorado Fuel Cell Center
 Power Electronics for Hybrid Renewable System
 Solar (PV materials, thermal, systems)
 Wind
Center for Space Resources
– Insitu resource utilization
– Lunar, Martian exploration
Geo-Sciences/Mining
Environmental Sciences/Hydrology
“Intelligent” Geosystems
EE and CARDI Activities
Kevin L. Moore, Colorado School of Mines
EE Research Areas and Applications
COLORADO SCHOOL OF MINES
Power
Systems
Renewable
Energy
Power
Electronics
Signal and
Image
Processing
Robotics
Wireless
Communications
Control Systems
Kevin L. Moore, Colorado School of Mines
Humanitarian
Engineering
EE Research Areas and CSM’s Mission
• RoboticCOLORADO
welding SCHOOL OF MINES
• Welding process control
• Control of plasma processes
• PV manufacturing process control
EARTH’S REOURCES
• Discovery and
recovery
MATERIALS
• Utilization in advanced
processes and products
• Robotics for mining
- Image processing
• Mine safety
- Control systems
- Sensor networks
ENERGY
• Generation, conversion,
and distribution
• Power transmission and distribution
• Renewable energy
- Wind power
- Fuel cell control
- Hybrid power system coordination
• Humanitarian engineering
Kevin L. Moore, Colorado School of Mines
• Robotics for security applications
• Biomedical engineering
- Image processing
ENVIRONMENT
• Economic and social systems
necessary to ensure prudent
and provident use of
resources in a sustainable
global society
Center for Robotics, Automation, and
Distributed Intelligence (CARDI)
COLORADO SCHOOL OF MINES
• CSM research center focused on
– Control systems, robotics, sensing (especially vision) and
communication networks, machine learning and intelligence,
ad hoc mobile networks, sensor networks
• Applications to problems of concern at CSM, including:
– Environment, energy, natural resources, materials,
transportation, structures, geotechnical, information,
communications, networking, medicine, and data mining
• Problems requiring multi-disciplinary systems approach to
integrate technologies from the different disciplines
– 14 faculty
– Electrical, mechanical, civil, computer science, mathematics
Kevin L. Moore, Colorado School of Mines
CARDI Research Areas and Applications
COLORADO SCHOOL OF MINES
Biomedical
Environment
3D Stereo Mapping
Medical
Imaging
Robotics
Sensor Networks
Control
Stereo-Vision for
Welding Automation
Wind Turbine
Control
Mobile Ad-hoc Networks
Communications
Automation
Reconfigurable
Wireless Nodes
Control of
Plasma
Processes
Manufacturing
Kevin L. Moore, Colorado School of Mines
Distributed Intelligence
Activity
Identification
Data Mining
CSM Control Systems-Related Research
COLORADO SCHOOL OF MINES
• CSM EE/ME/CE/CARDI faculty conduct both theoretical and applied
research in control systems:
– Fault detection and identification (Vincent)
– Control of material processing (Moore, Vincent)
– Autonomous systems and robot control (mobile, arms, and mobile arms) (Moore,
Steele, Vincent, Hoff)
– Coordinated control for robotics and UAVs (Moore)
– Vision-based navigation and control (Moore, Vincent, Hoff)
– Augmented reality (Hoff, Vincent)
– Intelligent sensing for geo-systems applications (Mooney)
– Sensor networks (Moore, Weiss, Colagrosso)
– Welding control (Hoff, Moore, Steele, Vincent)
– Learning control, intelligent control (Moore, Simoes)
– Adaptive control (Johnson)
– Wind energy applications (Johnson)
– Distributed coordination/control of renewable energy (Johnson, Simoes)
– Power electronics for hybrid energy control (Simoes)
– Fuel cell system controllers (Moore, Simoes)
– System engineering (Moore, Steele)
Kevin L. Moore, Colorado School of Mines
Outline
COLORADO SCHOOL OF MINES
•
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Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
CSM Robotics
COLORADO SCHOOL OF MINES
• CSM has a long legacy of robotics-related activity
• CSM faculty and staff have significant robotics-related expertise
– Mechanism Design
– Robotic Manipulators
– Mobile Robots
– Cooperative robotics
– UAVs
– Vision-based robotics; Augmented reality
– User Interfaces
– System engineering
– Applications: mining and lunar exploration
– Commercialization
Kevin L. Moore, Colorado School of Mines
CSM Robots
COLORADO SCHOOL OF MINES
Martin Marietta BatMobile
NASA Contest
Concept design for
In-situ resource
utilization
NSF REU Arm
Kevin L. Moore, Colorado School of Mines
SAE Walking Machine
Weederbot III
COLORADO SCHOOL OF MINES
2005
Senior Design
(supervised by John Steele)
Autonomous Mower Project
Kevin L. Moore, Colorado School of Mines
2006
Mobile Manipulators (Mobile ARMS)
COLORADO SCHOOL OF MINES
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Human-robot interaction
Autonomous Pick-and-Place
Visual Servoing
Based on the
ODIS Platform
used in theatre
Kevin L. Moore, Colorado School of Mines
3D Models for Navigation and Manipulation
COLORADO SCHOOL OF MINES
Robotics can be
used to
automate
load/haul/dump
vehicles
Automation of Load/Haul/Dump
• Remove miners from operating area
Stereo vision is used for
• Guidance
• Map building
• Collision avoidance
50m Long Mine Model
(green from laser ranger, yellow from stereo)
Kevin L. Moore, Colorado School of Mines
Faculty: Steele and Vincent
Autonomous Robots built by Kevin Moore’s Team at
Utah State
COLORADO SCHOOL OF MINES
T1 -1998
T2 -1998
ODIS I -2000
T4 -2003
T3 -1999
Kevin L. Moore, Colorado School of Mines
(Hydraulic drive/steer)
Autonomous Tractors and Unique Mobility Robots built
by Kevin Moore’s Team at Utah State
COLORADO SCHOOL OF MINES
Automated Tractor Projects
(CSOIS Spin-Off, Autonomous Solutions, Inc.)
Unique Mobility Robots
Kevin L. Moore, Colorado School of Mines
COLORADO SCHOOL OF MINES
“Putting Robots in Harm’s Way So People Aren’t”
ODIS – the Omni-Directional Inspection System
An ODV Application: Physical Security
Kevin L. Moore, Colorado School of Mines
From Intelligent Behavior to
Cooperative Autonomy…
COLORADO SCHOOL OF MINES
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Seek a single machine that can do both of the following tasks via semantic (verbal)
instruction from a (human) supervisor:
Load a trailer
Cooperatively weld a pipe
• Humans can do this!
• How do we make a group of robots that can also do this?
Kevin L. Moore, Colorado School of Mines
Mote-Based Distributed Robots
COLORADO SCHOOL OF MINES
Prototype
plume-tracking
testbed developed
by Moore at USU
Robotic wireless
networks for
remote video
streaming - Weiss
Kevin L. Moore, Colorado School of Mines
Wireless 802.11g Video Streaming through a Robot MANET
COLORADO SCHOOL OF MINES
Laptop and Starting Position
Laptop
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2
1
~2m
Hallway 1
(~6m)
Robot Monitoring
Software on
Laptop
(video feed from
lead robot on
upper right)
3
Hallway 2
(~20m)
2
Hallway 3
(~10m)
Stopping positions of robots
(blue dots)
Lead Robot with Video Camera
1
Kevin L. Moore, Colorado School of Mines
Faculty: Weiss
Outline
COLORADO SCHOOL OF MINES
•
•
•
•
•
Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
Other Control-Related Research
COLORADO SCHOOL OF MINES
• Faculty conduct both theoretical and applied research in
areas related to robotics and control systems:
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Welding Control (Moore, Vincent, Steele)
Material Processing (Moore, Vincent)
Intelligent Sensing and Control (Mooney, Steele)
Computer Vision (Hoff, Vincent)
Wireless system design (Weiss)
Sensor networks (Colagrosso, Moore, Weiss)
Kevin L. Moore, Colorado School of Mines
Robotic Welding
COLORADO SCHOOL OF MINES
Rectified Stereo Image Pair
Faculty: Steele, Vincent, and Hoff
Derived surface of weld pool
Kevin L. Moore, Colorado School of Mines
Welding Control and Control of Material
Processing
COLORADO SCHOOL OF MINES
• Control of Materials Processing
– Foundry Cupola
– Gas Metal Arc Welding
– PV Material Manufacturing
Kevin L. Moore, Colorado School of Mines
Smart Bit Technology: Force Sensing for
Manipulation (Steele)
COLORADO SCHOOL OF MINES
Sensory Goals
• In-Situ measurements
• Bit wear indicator
• Horizon detection
• Performance indicators
• Improve Mind-Machine link
(20-mile Longwall)
(Continuous Miner)
Kevin L. Moore, Colorado School of Mines
Equipment Application
• Radial borers
• Continuous miners
• Longwall shearers
Mike Mooney
Intelligent
Soil Compaction
(funded by NSF & NCHRP)
COLORADO SCHOOL OF MINES
Objectives:
(1) Develop the relationships between
vibration properties of roller
compactor and underlying soil
properties relevant to design
(2) Improve our understanding of
how feedback control might improve
soil compaction
(3) Improving parameter estimation
via geolocation data, multiple passes,
etc.
Forward
eccentric
accelerometer
V = 2-4 m/s
200-300 mm soil
Layers of previously
compacted soil; possible
near surface bedrock
Kevin L. Moore, Colorado School of Mines
Iterative Learning Control (Moore)
COLORADO SCHOOL OF MINES
• Paradigm for systems that operate repetitively
Current Trial's
Input
Current Trial's
Output
Plant
Next Trial's
Input
Iterative
Learning
Controller
Desired
Output
uk 1 (t )  uk (t )  f ( yd (t 1)  yk (t 1))
Kevin L. Moore, Colorado School of Mines
Iterative Learning Control Applications
COLORADO SCHOOL OF MINES
• Iterative Learning Control
– Paradigm for controlling systems that repeat the same
operation over and over
• New applications
– Develop new approach called multi-pass ILC
– Vision-based ILC (also for multi-pass problems)
– nD ILC (e.g., irrigation control)
Kevin L. Moore, Colorado School of Mines
Vision/User Interface; Augmented Reality
(Hoff)
COLORADO SCHOOL OF MINES
A system to
recognize gestures,
for the purpose of
robot control
Constructing scene models
from stereo vision
Augmented reality system
developed at CSM
Kevin L. Moore, Colorado School of Mines
Registration of
range data
Activity Identification and
Visualization (Hoff)
COLORADO SCHOOL OF MINES
Problem: Detect and identify unusual or
suspicious activities in surveillance
data
Cars and
bicycles are
labeled
green and
yellow
Statistical measures (eg, chi-square)
signal how unusual a track is from
the rest of the scene, and compare
two scenes
Interactive visualization tools enable
analyst to pick salient features for
machine learning
Person
handing
out flyers is
labeled red
Faculty: Hoff and Lee
Kevin L. Moore, Colorado School of Mines
Outline
COLORADO SCHOOL OF MINES
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Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
Research in telecommunications focuses
on mobile computing and networking
COLORADO SCHOOL OF MINES
• Research areas:
– How to connect mobile
computers (laptops,
palmtops, etc) to the Internet
– How to create ad hoc
networks on demand
• one unit may be connected to
some wired network
• how to create and maintain
network connectivity
• previous infrastructure is
demolished or non-existent
– Quality of service
Faculty: Camp, Navidi, Colagrosso, Liu
Kevin L. Moore, Colorado School of Mines
Potential Applications of Ad Hoc Networks
COLORADO SCHOOL OF MINES
Kevin L. Moore, Colorado School of Mines
Autonomously Reconfigurable Systems
COLORADO SCHOOL OF MINES
• Consider an underground mine
Legend:
Flows of people, material
Flows of air
Toxic gas
Kevin L. Moore, Colorado School of Mines
Flow of information
Fixed radio node
Mobile radio node
Add sensors and flows of people, material, and air
Legend:
Flows of people, material
Flows of air
Toxic gas
Flow of information
Fixed radio node
Mobile radio node
Suppose a hazardous gas develops
Legend:
Flows of people, material
Flows of air
Toxic gas
Flow of information
Fixed radio node
Mobile radio node
The system should autonomously-reconfigure to
redirect flows of people, material, and air
Legend:
Flows of people, material
Flows of air
Toxic gas
Flow of information
Fixed radio node
Mobile radio node
COLORADO SCHOOL OF MINES
Kevin L. Moore, Colorado School of Mines
Sensor node
VDSL node
Phone cable
See live demo at
http://ore.mines.edu/~mcolagro/edgarmine/
Outline
COLORADO SCHOOL OF MINES
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Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
Control-Related Energy Research at CSM
COLORADO SCHOOL OF MINES
• The Electrical Engineering group at CSM is involved
in three main areas of electrical energy research
– Distribution and transmission
– Control and coordination
– Power electronics
• Other faculty in the Engineering Division and other
CSM departments are also involved in electrical
energy generation research.
Kevin L. Moore, Colorado School of Mines
The future of electrical energy
COLORADO SCHOOL OF MINES
• Energy will be
introduced to the
grid from a variety
of sources
• Distributed
generation with
non-traditional
resources is less
predictable and
more difficult to
control
• Could eventually
see emergence of
the “smart grid” or
“Enernet” (energy
network)
Kevin L. Moore, Colorado School of Mines
Figure courtesy of Ben Kroposki (National Renewable Energy Laboratory),
and Janet Ginsburg (“Reinventing the Power Grid” in Business Week, February
26, 2001 pp.106-107).
CSM Electrical Faculty Energy Research
Interests
COLORADO SCHOOL OF MINES
• A key factor for clean, efficient energy is management and control
• Specific CSM EE area of interests include:
– Control of distributed and conventional generation sources and
associated manufacturing processes
 Turbine control in wind; balance-of-plant control in fuel cells;
combined thermal/power management systems in concentrating solar
power; PV manufacturing
– Control of power flow in hybrid energy systems
 Coordination of turbines in a wind farm; “smart” inverters/converters
– Control of power flow into and out of the grid
 Anti-islanding/ prevention of cascading failures/“robust grid”; power
quality/reliability; grid synchronization
– Economically-driven grid/resource management
 “Smart grid”; “Ener-net” = Energy + Network
Kevin L. Moore, Colorado School of Mines
Photovoltaic Solar Collector Field
The “Grid”
COLORADO SCHOOL OF MINES
PV Field
Sensor Network
and Controller
Switching/Inverter
Substation & Power Conditioning
Thermal Solar Energy
Collector Field
Auxiliary
Storage
Power Plant
(Steam or Direct-to-H2)
Integrated Roof w/
Thermal/PV Solar Energy
Load
Balancing
Fuel Cells
SCADA System
Smart Data Bus
Control Room
Kevin L. Moore, Colorado School of Mines
Wind and Other Non-Solar
Renewable Energy Generation
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Photovoltaic Solar Collector Field
• PV Manufacturing
– Tyrone Vincent
COLORADO SCHOOL OF MINES
– Bob Kee
• Fuel Cell Control
– Marcelo Simoes
– Kevin Moore
• Wind Turbine/Wind
Farm Control
– Katie Johnson
– Marcelo Simoes
– Kevin Moore
Kevin L. Moore, Colorado School of Mines
Fuel Cells
Wind and Other Non-Solar
Renewable Energy Generation
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• Substation-to-Grid Transmission
COLORADO SCHOOL OF MINES
– P.K. Sen
– Sid Suryanarayanan
• Auxiliary Units-to-Substation
Transmission
– P.K. Sen
– Sid Suryanarayanan
Kevin L. Moore, Colorado School of Mines
• Microgrids
– Marcelo SimoesCOLORADO SCHOOL OF MINES
– Sid Suryanarayanan
• Inverter Power
Electronics
– Marcelo Simoes
Switching/Inverter
Substation & Power Conditioning
Auxiliary
Storage
• Auxiliary Storage/Load
Balancing/Coordination
– Marcelo Simoes
– Katie Johnson
– P.K. Sen
– Kevin Moore
Kevin L. Moore, Colorado School of Mines
Load
Balancing
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PV Field
Sensor Network
and Controller
SCADA System
Smart Data Bus
Kevin L. Moore, Colorado School of Mines
COLORADO SCHOOLand
OF MINES
• Instrumentation
Control: Smart Grids
– Marcelo Simoes
– Kathryn Johnson
– Kevin Moore
– Tyrone Vincent
– P.K. Sen
– Sid Suryanarayanan
Control applications in PV
materials processing (Vincent, Kee)
COLORADO SCHOOL OF MINES
We have worked with major PV suppliers
• ITN Energy Systems (Littleton, CO)
• Global Solar (Tucson, AZ)
• First Solar (Perrysburg, OH)
• Ascent Solar (Littleton, CO)
• PrimeStar Solar (Golden)
Thin film technologies
• Copper-indium-gallium-diselenide (ITN, Global, Ascent)
• Cadmium-telluride (First Solar, PrimeStar)
Modeling and design capabilities
• Thermal systems
• Chemically reacting flow
• Model-based process control
Kevin L. Moore, Colorado School of Mines
Theoretical Basis: Structured Nonlinear
System Identification
COLORADO SCHOOL OF MINES
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Goal: Identification of components in an interconnected system
Kevin L. Moore, Colorado School of Mines
First-Solar’s CdTe process is based on a
particle-injection CVD process
COLORADO SCHOOL OF MINES
Glass substrate
Kevin L. Moore, Colorado School of Mines
Modeling and simulation support design and
control enhancement of the CIGS process
COLORADO SCHOOL OF MINES
Plume models
• Direct Simulation Monte Carlo
• Beam shape on web
• Haystacking near nozzles
Transition flow models
• Gas dynamics in nozzles
• Propensity for spit formation
Melt-pool convection
• Buoyancy and surface-tension
• Flow instabilities
Thermal models
• Three-dimensional finite element
• Conduction and radiation
Control strategies
• Model-based control
Kevin L. Moore, Colorado School of Mines
Identification and modeling play an important role
in developing advanced control architectures
COLORADO SCHOOL OF MINES
Kevin L. Moore, Colorado School of Mines
Hybrid Power Control for Renewable Energy
Kathryn Johnson)
(
COLORADO SCHOOL OF MINES
• Wind turbine optimization and
control
– adaptive controller validated both
in simulation and field tests
– annual increase in energy of more
than 5%
• Control of hybrid renewable energy
systems
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solar
wind
fuel cells
batteries
hydrogen
Kevin L. Moore, Colorado School of Mines
Turbine
Model
Wind
Input
Adaptive
Controller
Adaptive Torque Control of Variable Speed Wind
Turbines
COLORADO SCHOOL OF MINES
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1000
Wind
Turbine: Standard Control
Turbine: Adaptive Control
Power (kW)
800
•
600
400
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200
0
0
5
10
15
Wind Speed (m/s)
20
25
Turbine is
stopped when
wind is too slow
or too fast.
Turbine power is
limited in
moderately high
winds.
Adaptive control
can increase
turbine power in
lower wind
speeds.
Energy capture can be increased by 5 – 6%,
leading to a similar decrease in cost of wind
energy.
Faculty: Johnson
Kevin L. Moore, Colorado School of Mines
Non-trivial interconnection
to the distribution grid
COLORADO SCHOOL OF MINES
Must be fault-tolerant and
refrain from contributing
to grid faults
Multiple control levels
Kevin L. Moore, Colorado School of Mines
Multi-Resolution
Wind Farm
Simulator
Wind Farm
Grid
Substation
Storage
SCADA/
Power Electronics
Hardware-in-the-loop
Models of Grid and
Grid Interconnection,
COLORADO SCHOOL OF MINES
possibly with SCADA
Hardware-in-theLoop using RTDS
Dedicated Simulation
System
Load
Models of Turbines, Substation and Power
Electronics, Storage and Voltage Control,
and Control Systems Simulated using
Power-Industry Standard Software such as
PSCAD and MATLAB
CFD Models of Turbine Blades Simulated for
Realistic Wind Velocity Flow Fields using
Golden Energy Computing Organization’s 10+
teraflop Linux cluster
Kevin L. Moore, Colorado School of Mines
Power Electronics and Control (Marcelo Simoes)
COLORADO SCHOOL OF MINES
Research Theme: Intelligent Control for Energy Conversion
and Interconnection of Renewable Energy Systems
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Power electronics for efficient energy conversion
Intelligent control as applied to energy conversion
Modeling and control of microgrids
Methods and systems for maximum photovoltaic energy capturing and
conditioning
Wind turbine variable speed systems
Energy storage for renewable energy conditioning
Hybrid renewable energy systems
Fault tolerant systems for interconnection of renewable energy to the
grid
Kevin L. Moore, Colorado School of Mines
Transient Storage Compensation of Fuel
Cells Response with Batteries
COLORADO SCHOOL OF MINES
Bi-Directional Power Converter:
M. Michon, J.L. Duarte, M. Hendrix and M. Godoy Simões, “A three-port bi-directional converter for hybrid fuel cell systems” 35th
IEEE Power Electronics Specialists Conference (PESC), Aachen, Germany, June 20-25, 2004
Kevin L. Moore, Colorado School of Mines
Coordinated Balance-of-Plant/ Hybrid Power System
Components Control for Fuel-Cell Based Systems
COLORADO SCHOOL OF MINES
• Typical application treats the fuel cell, auxiliary
components, and load separately:
Kevin L. Moore, Colorado School of Mines
Coordinated Balance-of-Plant/ Hybrid Power System
Components Control for Fuel-Cell Based Systems
COLORADO SCHOOL OF MINES
• Bi-Directional power converter enables coordinated approach:
Kevin L. Moore, Colorado School of Mines
Toward the “EnerNet” of the Future
COLORADO SCHOOL OF MINES
Every home
a micro-grid
Wind
Today’s grid evolves
to a large(r)-scale
(than today) complex
adaptive system
Fuel Cell
Power
Solar
Storage
Data
Wind
Central
Generation
Gas Gen
Fuel Cell
Solar
Storage Gas Gen
Wind
Fuel Cell
Solar
Wind
Fuel Cell
Storage Gas Gen
Solar
Wind
Fuel Cell
Storage Gas Gen
Solar
Storage Gas Gen
Cooperative
Generation
Wind
Fuel Cell
Solar
Wind
Fuel Cell
Solar
Storage Gas Gen
Kevin L. Moore, Colorado School of Mines
Wind
Fuel Cell
Solar
Storage Gas Gen
Storage Gas Gen
Central
Generation
COLORADO SCHOOL OF MINES
Credit: Damon Dougherty – Industry Manager, Intergraph
Kevin L. Moore, Colorado School of Mines
Outline
COLORADO SCHOOL OF MINES
•
•
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Introduction
Robotics
Other Control-Related Research
Sensor Networks
Renewable Energy-Related Control Research
Kevin L. Moore, Colorado School of Mines
New Directions -1
COLORADO SCHOOL OF MINES
Robotic Material Handling and Processes
in Mining Applications
• Processes Characterized by Force Interaction
Between Actuators and Materials
• Automated load-haul-dump (LHD) vehicles
• Automated shoveling in open-pit mining
• Downstream operations that are dirty,
difficult, dull, or dangerous
– Material loading to/from rail cars
– Robotic search and rescue
 Rubble clearing
 Airhole boring
Robotic Applications in Oil and Gas
• Robotic roustabout
• Automated maintenance of oil derricks
Kevin L. Moore, Colorado School of Mines
Automated LHD system
developed at CSM
New Directions -2
COLORADO SCHOOL OF MINES
Robotic Welding Systems
• Mobile (or portable) robotic welding systems
– Service and repair industry focus
– Shipbuilding and construction
• On-line fault detection and diagnostics
• Focus on infrastucture applications
– Outdoors
– Hazardous
– Heavy industry
• Robotic pipefitting applications
Kevin L. Moore, Colorado School of Mines
Robotic welding system at CSM
New Directions -3
COLORADO SCHOOL OF MINES
Mobile manipulation and mobile robots integrated with
building automation infrastructure and other data bases
• Medical facility and security applications
• Virtual presense for quarantined patients (idea from
National Institues for Medical Infomatics Media
Lab (http://www.imedi.org/docs/references/mr.htm)
– Sterilizing floors (an enhanced Roomba)
– Delivering lab specimens (like the little robots
zipping around the DeathStar in Star Wars)
– Pulling patients on stretchers to rooms
– Performing perfect CPR
– Performing basic aspects of the physical exam
(looking at pupils, listening to lungs and heart)
– Etc.
Kevin L. Moore, Colorado School of Mines
• Patient manipulation:
RIMAN Robot (Japan)
New Directions -4
COLORADO SCHOOL OF MINES
Patient-specific rehabilitation and therapeutic robotics
Interrogation and
characterization of
injury
Patient
specific
model
Model-based
patient-specific
therapy prescription
Therapeutic program
specification for
rehabilitation robot
Kevin L. Moore, Colorado School of Mines