The questions for the final exam
will BE DERIVED from the following (i.e., they may differ slightly). The exam
is closed everything. Also, since you have these questions three weeks in
advance, no questions regarding the exam will be answered prior to the exam (from
the time you receive this) Also, the point value of each question will not be
revealed until you receive the actual exam on test day.
EGR/CS
434
Artificial Intelligence and Robotics
Final
Exam
Fall, 2009
Dr. Wunderlich
This is a closed-book, closed-notes exam (and
no calculators are allowed). Write your answers on the blank paper
supplied to you (write your name at the top of every page).
MACHINE
INTELLIGENCE (PART A)
RECALLING LECTURE AND
HANDOUTS (no electronic version), ANSWER THE FOLLOWING:
#
(X points): Describe what each of the following historic Expert Systems
does:
A.
DENDRAL
B.
MYCIN
C.
PROSPECTOR
D.
INTERNIST
# (X points): List and describe the
three major deficiencies of symbolic A.I. expert systems (i.e., emphasized by
Dr. W. in lecture notes).
#
(X points): List and describe
the four major types of symbolic A.I. expert system problems (i.e., emphasized
by Dr. W. in lecture notes).
# (X points): Describe
“Backward-chaining” in symbolic A.I. expert systems.
# (X points): Describe
what each of the following does in a symbolic A.I. expert system:
A.
Explanation
Subsystem
B.
Knowledge
Base
C.
Knowledge
Base Editor
D.
Inference
Engine
#
(X points): Draw a complete “And/Or graph” for
the following symbolic A.I. expert system discussed in lecture defined by the
following rules:
A.
If
engine is getting gas and the engine will turn over, then the problem is spark
plugs.
B.
If
engine is does not turn over and the lights do not come on, then the problem is
battery or cable.
C.
If
engine is does not turn over and the lights do come on, then the problem is
starter motor.
D.
If
there is gas in the fuel tank and gas in the carburetor, then the engine is
getting gas.
# (X points): Draw a complete “And/Or graph” for a symbolic A.I. expert system defined by
the following rules:
A.
If
. . . . . , then . . . . .
B.
If
. . . . . , then . . . . .
C.
If
. . . . . , then . . . . .
D.
If
. . . . . , then . . . . .
# (X points): Recalling Dr. W’s
symbolic A.I. expert system “Advise Callers to a Doctor’s Office,” do:
A.
Describe
the important assumptions and possible ethical and legal ramifications of them.
B.
Do
one of the following (and state which one you are doing):
1.
Draw
the And/Or graph for Dr. W.’s design
2.
Create
you own rules, user input, etc. and draw your own And/Or graph
#
(X points): Compare in your own words “Probability Theory” vs. “Uncertainty
Theory” for symbolic A.I. expert systems.
# (X points): Concerning
confidence values used in Expert Systems:
A.
List the equation for a “Certainty Factor,” and list
the three laws (equations) relating to it
B.
Using these equations, calculate the following (show
your work) . . . . . . .
#
(X points): Describe the two places confidence values are used in
Expert Systems
#
(X points): Describe how Baye’s
theorem of Probability was applied to the “Copper Mining” problem discussed in
class.
# (X points): Recalling
Dr. W’s symbolic A.I. expert system “Selecting a Toy for a Child,” do:
A.
Describe
the significance of the Confidence values used for both the rules and the user
inputs.
B.
Draw
the And/Or graph
MACHINE
INTELLIGENCE (PART B)
IN REFERENCE TO THE FOLLOWING TALK AND PAPERS:
·
TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_MACHINE_INTELLIGENCE.pdf
·
Wunderlich,
J.T. (2003). Defining the limits of machine intelligence. In Proceedings of IEEE SoutheastCon,
Ocho Rios, Jamaica, [CD-ROM]. IEEE Press.: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_SUBMITPAPERdefininglimitsREVISED16b.pdf
·
Wunderlich,
J.T. (2004). Top-down vs. bottom-up neurocomputer
design. In Intelligent Engineering
Systems through Artificial Neural Networks, Proceedings of ANNIE 2004
International Conference, St. Louis, MO. H. Dagli
(Ed.): Vol. 14. (pp. 855-866). New York, NY: ASME Press: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_SUBMIT_FINAL_ANNIE2004_WUNDERLICH_61_TO_PRINT_fixed_after.pdf
·
Wunderlich, J.T. (2008). Two single-chip neurocomputer designs; one bottom-up, one top-down. (invited journal paper in peer-review): http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_NNjournal19_SUBMIT_without_letter.pdf
ANSWER THE FOLLOWING:
# (X points): Discuss how symbolic AI differs from
artificial neural networks for each of the abilities listed here:
Reduced Mental Ability Matrix (i.e., reduce from the
42 abilities given in class)
|
|
|
Can human do? |
Can bug do? (spider) |
Can Conventional Computer Program do? |
Can Symbolic AI Program do? |
Can Artificial Neural Network do? |
Comments |
|
|
BASIC ANIMAL ABILITIES: |
|
|
|
|
|
|
|
3 |
Learn and adapt
|
yes |
yes |
no |
somewhat |
yes |
Evolution |
|
13 |
Generalize
|
yes |
somewhat |
no |
somewhat |
yes |
|
|
14 |
Associate
|
yes |
yes |
somewhat |
somewhat |
yes |
|
|
15 |
Recognition
patterns |
yes |
yes |
somewhat |
somewhat |
yes |
|
|
16 |
Robust
under partial failure |
yes |
yes |
no |
no |
yes |
|
|
19 |
Stability,
repeatability, predictability |
somewhat |
somewhat |
yes |
yes |
somewhat |
Uncertainty |
|
20 |
Multitask
|
yes |
yes |
yes |
no |
yes |
|
|
|
COMPLEX ABILITIES: |
|
|
|
|
|
|
|
21 |
Abstraction |
yes |
unlikely |
no |
no |
somewhat |
|
|
25 |
Heuristics |
yes |
yes |
somewhat |
yes |
no |
|
|
26 |
Inference |
yes |
yes |
somewhat |
yes |
somewhat |
|
|
27 |
Hypothesis
testing |
yes |
somewhat |
somewhat |
yes |
no |
|
|
29 |
Ethical
behavior |
yes |
unlikely |
no |
somewhat |
somewhat |
If
coded/trained |
|
31 |
Open
to inspection |
somewhat |
somewhat |
yes |
yes |
somewhat |
|
#
(X points): Briefly describe the conceptual difference between
"Top-down" and "Bottom-up" neurocomputer
design.
1.
Describe
the importance of maintaining high-precision for the neuron transfer function
during learning.
2.
Compare
and contrast Dr. W’s various numerical methods used to approximate the neuron
transfer function (just the basic concepts – don’t reproduce all equations).
3.
Why
bother to attempt on-chip learning?
4.
Why
is a polynomial a good idea for neuron transfer function implementation?
RECALLING LECTURE AND
HANDOUTS ON NEURAL NETWORKS (no electronic version), ANSWER THE
FOLLOWING:
#
(X points): List any two of the 10 parts
of the human brain identified in lecture
and discuss the function of each.
# (X points): What is the function of a dendrite.
# (X points): List
and describe the function of the 3 different types of neurons discussed in
lecture.
# (X points): Define
Proprioception.
# (X points): List the three
observations of the human brain made by William James in 1890.
# (X points): Write Hebb’s 1949 statement on learning.
#
(X points): In discussing all of the
historical developments that eventually led to the back-propagation neural
network
model, briefly describe one
significant contribution of each of the
following individuals:
A.
1943
McCullah and Pitts
B.
1949
Hebb
C.
1958
Selfridge
D.
1960
Rosenblatt
E.
1974
Werbos
F.
1986
Rumelhart
#
(X points): Draw a picture of and explain the functioning of (with
equations and words) the significant computational architecture defined
by McCullah and Pitts in 1943.
#
(X points): Compare and contrast (with both sketches and words):
A.
Rosenbaltt’s 1960 PERCEPTRON
B.
Rumelhart et al. ‘s 1986
BACK-PROPAGATION
# (X points): Concerning the research of the Physicist J.J.
Hopfield:
A.
How did his 1982 neural network model’s learning
differ from other models such as backpropagation.
B.
What did he contribute in 1984 that significantly
changed the functioning of other neural network models to follow.
Explain the significance of this contribution.
#
(X points): Discuss a type of Neural Network different from backpropagation and discuss how it differs.
# (X points): In
1969, Minsky and Papert
made a significant observation about neural networks regarding their ability to
deal with linear separability. Define linear separability and compare using tables and graphs the
difference between the binary “AND” function and the binary “XOR” function with
regards to Minsky and Papert’s
observations. What development in neural
networks solved this dilemma?
# (X points): Concerning
neurons,
A.
Sketch
and label a graph of the action potential of a biological neuron
B.
Sketch
and label a graph of the hard-limiter transfer-function used in artificial
neural networks.
C.
Sketch
and label a graph of the sigmoid transfer-function used in artificial neural
networks.
D.
Which
of (b) or (c) is more like (a) and why.
E.
What
is it about the sigmoid transfer-function that makes it desirable for
back-propagation learning
# (X points): Concerning
artificial vs. biological Neural Networks,
A.
Sketch
and label a graph of the action potential of a biological neuron
B.
Describe
the basic functioning of the human brain and a biological neuron in your own
words (electrical and chemical concepts would enhance your answer, but are not
required).
C.
Sketch
and label a graph of the sigmoid transfer-function used in artificial neural
networks.
D.
Describe
the basic functioning of backpropagation neural
networks (learning and otherwise) in your own words.
#
(X points): In gradient decent learning, describe the import concept
involved in:
A.
Varying
the learning rate and how it relates to the topology of the error-surface
B.
The
importance of using a continuously differentiable neuron transfer function and
how the instantaneous-slope of this function can effect
learning.
# (X points): Using
the Quotient Rule, find the derivative of:
# (X points): Find
dy/dx for:
# (X points): Describe
in your own words and sketches (no equations), the method of “Least
Squares”
#
(X points): Describe in your own words and sketches (no
equations), Gradient Descent learning (including how the error surface is
created)
#
(X points): Sketch and label a graph of the typical sigmoidal
neural network transfer function, then sketch and label a graph of it’s derivative. Then exp[lain how
the magnitude of the derivative effects neural network backpropagation
learning.
#
(X points): Given the following neuron transfer functions:
and error (i.e., “cost”) function:
derive using Calculus (i.e., the chain rule, partial
derivatives, the quotient rule, etc.) an equation for changing the weights
between the hidden layer and the output layer of a three-layered (i, j, k) back-propagation neural network . Assume there are
no BIAS connections to the neurons. Simplify your final equation as much as
possible. Also, discuss how weight changes are magnified when output neurons
are at “sticking points”.
# (X points): Given
the following neuron transfer functions:
and error (i.e., “cost”) function:
derive using Calculus (i.e., the chain rule, partial
derivatives, the quotient rule, etc.) an equation for changing the weights
between the hidden layer and the output layer of a three-layered (i, j, k) back-propagation neural network. Assume there are
no BIAS connections to the neurons. Simplify your final equation as much as
possible.
# (X points): Given
the following neuron transfer functions: . . . . .
and error (i.e., “cost”) function: . . . . .
derive using Calculus (i.e., the chain rule, partial
derivatives, the quotient rule, etc.) an equation for changing the weights
between the hidden layer and the output layer of a three-layered (i, j, k) back-propagation neural network . Assume there are
no BIAS connections to the neurons. Simplify your final equation as much as
possible. Also, discuss how weight changes are magnified when output neurons
are at “sticking points”.
#
(X points): Why do you think much higher precision is needed for Neural
Network back-propagation computations during learning than after learning completed.
#
(X points): Recalling Dr.
W.’s neural network code:
1.
What is the stopping tolerance for? (i.e., “STOPtolerance”)
2.
Why do you think the learning rate can be set so
high for simple 2-input examples (i.e. 1 to 5 instead of typically much less
than 1 for complex applications)?
3.
Why is the learning rate (in this code or any other
code) more sensitive for the XOR example than the AND or OR?
#
(X points): In the matlab neural network toolbox example “Linear Design,” what
is the general concept of what this program is doing?
#
(X points): In the matlab neural network toolbox example “Character
Recognition,” what is the general concept of what this program is doing? How is
noise
addressed?
ROBOTIC
ARMS
IN REFERENCE TO THE FOLLOWING TALK, TEXT EXHERPTS, AND
PAPERS:
·
TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_SENSORS_&_NAVIGATION.pdf
·
TEXT EXHERPTS S. .
B. Niku, Introduction to Robotics:
Analysis, Systems, Applications, Prentice Hall, July 30, 2001. (ISBN: 0130613096)
·
Wunderlich,
J.T. (2001). Simulation vs. real-time control; with applications to robotics
and neural networks. In Proceedings
of 2001 ASEE Annual Conference & Exposition, Albuquerque, NM:
(session 2793), [CD-ROM]. ASEE Publications: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION14sim_vs_RT.pdf
·
Wunderlich,
J.T. (2004). Simulating a robotic arm in a box: redundant kinematics, path
planning, and rapid-prototyping for enclosed spaces. In Transactions of the Society for Modeling and
Simulation International: Vol. 80. (pp. 301-316). San Diego, CA: Sage
Publications:
http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_SIM6_046338_Wunderlich_original_PROOF.pdf
·
Wunderlich,
J.T., S. Chen, D. Pino, and T. Rahman
(1993). Software architecture for a kinematically
dissimilar master-slave telerobot. In Proceedings of SPIE Int'l Conference on Telemanipulator Technology and Space Telerobotics,
Boston, MA: Vol. (2057). (pp. 187-198). SPIE Press. Discussed in TALK above
ANSWER THE FOLLOWING:
#
(X points): Concerning Robotic Manipulators (Niku
Robotic Arms text handout, page 5), list any three advantages and any three
disadvantages of Robots.
#
(X points): Concerning Robotic Manipulator DEGREES OF FREEDOM and
referencing (Niku Robotic Arms text handout), and recalling Dr. W’s
publication: Wunderlich, J.T. (2004). Simulating a
robotic arm in a box: redundant kinematics, path planning, and
rapid-prototyping for enclosed spaces. In Transactions of the Society for Modeling and Simulation International:
Vol. 80. (pp. 301-316). San Diego, CA: Sage Publications:
1.
How
many Degrees Of Freedom do you need to position the end of a manipulator
anywhere in 3D space
2.
How
many Degrees Of Freedom do you need to position and orient an end-effector on the end of a manipulator anywhere in 3D space
3.
How
many Degrees Of Freedom does the human arm have.
Explain where they are and how they move.
4.
Name
SIX different things that can be optimized when you have “extra” degrees of
freedom (i.e., what can be done with the null-space)
#
(X points): Recalling Dr. W’s publication: Wunderlich, J.T. (2004). Simulating a robotic arm in a box: redundant kinematics, path
planning, and rapid-prototyping for enclosed spaces. In Transactions of the Society for Modeling and
Simulation International: Vol. 80. (pp. 301-316). San Diego, CA: Sage Publications
1.
What
is the main objective of the research
2.
What
obstacle avoidance technique is used
3.
How
is the null space used
#
(X points): Recalling Dr. W’s publication: Wunderlich, J.T. (2004). Simulating a robotic arm in a box: redundant kinematics, path
planning, and rapid-prototyping for enclosed spaces. In Transactions of the Society for Modeling and
Simulation International: Vol. 80. (pp. 301-316). San Diego, CA: Sage
Publications., describe in words the mathematical complexity of
attempting to control nine manipulator elbows simultaneously avoiding the walls
of an enclosure while the end-effector performs a
precise task along the walls of a work cell deeply embedded in the enclosure. (All using a velocity-control scheme).
#
(X points): Concerning Robotic Manipulators (Niku
Robotic Arms text handout, page 13), describe with both pictures and words the
three different types of reference frames used for manipulators.
#
(X points): Concerning Robotic Manipulators (Niku
Robotic Arms text handout, page 13and 14), describe two ways that a
teach-pendant can be used by a factory technician to define the operation of a
manipulator.
#
(X points): Concerning Robotic Manipulators (Niku
Robotic Arms text handout), list 5 different types of industrial manufacturing
applications discussed in lecture, and five 5 different types of non-industrial
manufacturing applications discussed in lecture.
#
(X points): Recalling Dr. W’s publication: Wunderlich, J.T. (2001). Simulation vs. real-time control; with applications to robotics and
neural networks. In Proceedings
of 2001 ASEE Annual Conference & Exposition, Albuquerque, NM:
(session 2793), [CD-ROM]. ASEE Publications.
1.
What
is the purpose of the Jacobian Matrix
2.
What
is the purpose of a unit-direction vector
#
(X points): Recalling Dr. W’s publication: Wunderlich, J.T., S. Chen, D. Pino, and T. Rahman (1993). Software architecture for a kinematically
dissimilar master-slave telerobot. In Proceedings of SPIE Int'l Conference on Telemanipulator Technology and Space Telerobotics,
Boston, MA: Vol. (2057). (pp. 187-198). SPIE Press.
1.
What
is the main objective of the research (i.e. who is it for and what will it do
for them)?
2.
What
is teleoperation?
MOBILE
ROBOTS
IN REFERENCE TO THE FOLLOWING TALK, COURSE TEXT, AND
PAPERS:
·
ROVER MECHANICS TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_ROVER_MECHANICS.pdf
·
NAVIGATION AND SENSORS TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_SENSORS_&_NAVIGATION.pdf
·
REQUIRED COURSE TEXT R. Siegwart and
I. Nourbakhsh, Autonomous mobile robots,
Massachusetts Institute of Technology, 2004. (ISBN: 026219502X)
·
Wunderlich,
J.T. (2001). Simulation vs. real-time control; with applications to robotics
and neural networks. In Proceedings
of 2001 ASEE Annual Conference & Exposition, Albuquerque, NM:
(session 2793), [CD-ROM]. ASEE Publications: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION14sim_vs_RT.pdf
·
Painter J. and Wunderlich, J.T. (2008). Wunderbot IV: autonomous robot for international
competition. In Proceedings
of the 12th World Multi-Conference on Systemics,
Cybernetics and Informatics: WMSCI 2008, Orlando, FL: (pp. 62-67): http://users.etown.edu/w/wunderjt/ITALY_2009/REPORT_Jeremy_Crouse_w4_JAUS_EGR494report.pdf
·
Coleman,
D. and Wunderlich, J.T. (2008). O3: an optimal and opportunistic
path planner (with obstacle avoidance) using voronoi
polygons. In Proceedings
of IEEE the 10th international Workshop on Advanced Motion Control, Trento,
Italy. vol. 1, (pp. 371-376). IEEE Press: http://users.etown.edu/w/wunderjt/ITALY_2009/REPORT_Jeremy_Crouse_w4_JAUS_EGR494report.pdf
·
Lister,
M. and Wunderlich, J. T. (2002). Digital communications for a mobile robot.
In Proceedings of IEEE SoutheastCon, Columbia, SC, [CD-ROM]. IEEE Press. http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_W0_COMM_Full%20Wunder2myrevision.pdf
·
Crouse,
J. (2008). The joint architecture
for unmanned systems: a subsystem of the wunderbot 4. Elizabethtown College research report: http://users.etown.edu/w/wunderjt/ITALY_2009/REPORT_Jeremy_Crouse_w4_JAUS_EGR494report.pdf
·
Painter,
J. G., Coleman, D.,
Crouse, J., Yorgey, C., and Wunderlich, J.T. (2008) Wunderbot 4 IGVC
report. Judged and published on-line by IGVC: http://www.igvc.org/design/reports/dr207.pdf
·
Boeing
Company and NASA (1971) LRV operations handbook. Document LS006-002-2H: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_LRV.pdf
·
Boeing
Company and NASA (1971) LRV operations handbook.
appendix A performance data. Document LS006-002-2H.: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_LRV_Performance_Data.pdf
·
Carsen, A., Rankin, J.,
Fuguson, D., and Stentz, A.
(2007). Global path planning on board the mars
exploration rovers. In Proceedings of the
ANSWER THE FOLLOWING:
#
(X points): Concerning Mobile Robots (Siegwart
Text Chapter 1 pages 8,9 ), name five fields of
expertise (in addition to some knowledge of kinematics, dynamics, and control
theory), that a mobile robot team should have.
#
(X points): Concerning Mobile Robot Locomotion (Siegwart
Text Chapter 2, page 13), name the three reasons that replicating nature is
extremely difficult.
#
(X points): Concerning Mobile Robot Locomotion (Siegwart
Text Chapter 2, page 17), list for each of the key issues of “Stability,”
“Ground-contact,” and “Type-of-Environment,” two important issues.
#
(X points): Concerning Mobile Robot Locomotion (Siegwart
Text Chapter 2 page, 17), list three advantages and two disadvantages of legged
robotic locomotion.
#
(X points): Concerning Mobile Robot Locomotion (Siegwart
Text Chapter 2 page, 18), describe “Static Walking”
#
(X points): Concerning Mobile Robot Locomotion, describe why you would
ever want a mobile robot to have Humanoid form.
#
(X points): Concerning Mobile Robot Locomotion (Siegwart
Text Chapter 2, and in ROVER MECHANICS TALK), Make a table with the following
column headings:
1.
“Maneuverability”
2.
“Controllability”
3.
“Stability(Static)”
4.
“Stability(Dynamic)”
5.
“Zero-Turning-Radius?”
6.
“Zero-Turning-Radius-in-it’s-footprint?”
7.
“Sketch
of wheel configuration with arrows drawn showing turning radius”
Then
compare a three wheeled robot of your choosing to both a standard
rear-wheel-drive car, and to the Wunderbot. Use “+” , “-“ , “~” to fill in table, and circle best in each
category.
#
(X points): Concerning Mobile Robot Kinematics (Siegwart
Text Chapter 3), list the five ways that a Mobile robot differs from a
manipulator.
#
(X points): Concerning Mobile Robot Perception (Siegwart
Text Chapter 4), describe Proprioceptive and Exteroceptive
sensing for mobile robots.
# (X points): Concerning Mobile Robot
Perception (Siegwart Text Chapter 4), describe Active and Passive
sensing for mobile robots.
#
(X points): Concerning Mobile Robot Perception (Siegwart
Text Chapter 4, page 91, table 4.1), list the seven classifications of sensors.
#
(X points): Recalling Siegwart Text Chapter 3), describe in words, and vector
diagrams the relationship between a humanoid robot watching out the window his
master’s back yard which includes a mobile robot mowing the lawn using
dead-reckoning and random paths while avoiding a bunny who is chasing a butterfly.
The Humanoid must awaken his master if the lawn is done, if the mobile robot
accidentally traps the bunny, or if the bunny catches the butterfly; And tells
the master with a hand-drawing the exact location of the bunny, butterfly, and
the mobile robot. Clearly identify all local-to-global (and maybe
global-to-local) mappings. And clearly identify all simulations vs. real-time
control activities (both artificial and biological).
#
(X points): Describe how “Dead Reckoning” works.
#
(X points): Describe how “Celestial Navigation” works.
# (X points): Concerning
Mobile Robot Planning and Navigation and referring to the publication: D. Coleman and J.T. Wunderlich, “O3: An optimal and
opportunistic path planner (with obstacle avoidance) using Voronoi
polygons,” 2007, pending acceptance to AMC 2008, discuss with
pictures and words the methodology of this path-planning. Include a discussion
of both the LOCAL and GLOBAL characteristics.
# (X points): Concerning
Mobile Robot Planning and Navigation and referring to the publication: Carsen, A., Rankin, J., Fuguson, D., and Stentz, A. (2007). Global path planning on board the mars exploration rovers. In Proceedings of the
# (X points): Describe
all of the sensors on the Wunderbot 4 and discuss
some of the complexities of the sensor fusion.
COMPUTING, NETWORKING, etc.
IN REFERENCE TO THE FOLLOWING TALKS AND PAPERS:
·
“UUV, AUV, and SWARMS” TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_AUVs_UUVs_and_Swarms.pdf
·
COMPUTING TALK: http://users.etown.edu/w/wunderjt/ITALY_2009/TALK_COMPUTERS.pdf
·
Wunderlich,
J.T. (2001). Simulation vs. real-time control; with applications to robotics
and neural networks. In Proceedings
of 2001 ASEE Annual Conference & Exposition, Albuquerque, NM:
(session 2793), [CD-ROM]. ASEE Publications: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION14sim_vs_RT.pdf
·
Campos,
D. and Wunderlich, J. T. (2002). Development of an interactive simulation
with real-time robots for search and rescue. In Proceedings of IEEE/ASME International conference on Flexible
Automation, Hiroshima, Japan: (session U-007). ASME Press: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_SrchRscBotsnSim_final2.pdf
·
Henderson,
S., Shreshtha, S., Wunderlich, J.T. (2004). A high speed AUV test platform
(submitted to military conference): http://users.etown.edu/w/wunderjt/ITALY_2009/REPORTandPHOTO_steveHendersonAQUABOT_SUBMITTED.pdf
·
Wunderlich,
J.T. (1999). Focusing on the blurry distinction between microprocessors and
microcontrollers. In Proceedings
of 1999
·
Wunderlich,
J.T. (2003). Functional verification of SMP, MPP, and vector-register
supercomputers through controlled randomness. In Proceedings of IEEE
SoutheastCon, Ocho Rios,
Jamaica, M. Curtis (Ed.): (pp. 117-122). IEEE Press: http://users.etown.edu/w/wunderjt/ITALY_2009/PUBLICATION_SUBMITcontrledRandSEcon.pdf
·
Wunderlich,
J.T. (1997). Random number generator macros for the system assurance kernel
product assurance macro interface. Systems Programmer's User Manual for
·
Patterson,
R.L.. and Hammoud,
Ahmad. (2004) Reliability of Electronics for Cryogenic Space Applications
Being Assessed. NASA
Research and Technology 2004: http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20050217239_2005219510.pdf
·
Bajracharya, M., Maimone, M.W., and Helmick, D. (2008). Autonomy
for mars rovers: past, present, and future. In Computer: December, 2008. (pp. 44-50).
ANSWER THE FOLLOWING:
#
(X points): Recalling all of the above:
A.
Discuss
the importance of “simplicity” in designing computing systems for autonomous missions
(cite NASA examples)
B.
Discuss
the importance of “comprehensive quality testing” of computing systems for autonomous
missions (cite NASA examples)
C.
Discuss
all of the important differences in
designing a real-time control system vs. a simulation