Crabbe's Research With Students
Click here for
a pdf version of Crabbe's CV.
(this is way out of date)
Students
While USNA is not a research university, it does provide research
opportunities to outstanding undergraduates. This page describes the
research performed by my students.
Elizabeth Gergal. 2020-2021.
Carter Burn. 2017-2018.
Andrea Howard
I co-advised Andrea in 2014-2015. She was interested in applying artificial intelligence techniques to political science problems. In particular, she built a Bayesean belief network modelling food insecurity in the middle east, particularly Oman. Her Trident project won the 2015 Trident prize.
William Henry and Reagan Sanders. 2011-2012.
Micah Akin
I advised Micah from 2006-2007. He was interested in
teleoperated robots that are controlled over the internet.
Publication
- Akin, M., Crabbe, F.L. Mobile Vehicle
Teleoperated Over Wireless IP U.S. Naval Academy Computer Science
Department, USNA-CS-TR-2007-02, 2007.
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Abstract:
This document describes an effort to create a low cost teleoperated vehicle
that is controlled via 802.11g Wifi and the Internet. It is unusual in that it
can be controlled at a great distance but yet is still inexpensive. The
appendices provide instruction on how to construct and operate the vehicle,
along with the necessary source code.
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Stephen McMath
I co-advised Stephen from 2004-2005. David
Joyner in Mathematics was his primary Advisor.
Publications
- McMath, S., Crabbe, F., Joyner, D. Continued fractions and Parallel
SQUFOF. International Journal of Pure and Applied Mathematics, 34(1),
pp. 19-38, 2007.
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Abstract:
This paper contains 3 new results:
1. A proof that the two-sided continued fraction of the normalized square
root (an important part of the SQUFOF algorithm) has several very
attractive properties - periodicity, a symmetry point corresponding to
a factorization of N, and so on (see Theorems 6, 8, and 9 for details).
2. A proof of the infrastructure distance formula, Theorem 11 below,
which is also an important part of SQUFOF. This is in some sense
well-known but a proof has not, as far as we can see, appeared in the
literature.
3. Empirical results comparing two techniques for parallelization of SQUFOF,
showing that while the multipliers method is superior for small numbers
of processors, it becomes less efficient per processor as the number of
processors increases. The segments method maintains its efficiency per
procesor as the number of processors increases, and thus is predicted
to be superior for large numbers of processors. |
- McMath, S.Parallel Integer Factorization Using Quadratic Forms U.S.N.A. Trident Scholar project
report; no. 339 (2005)
Brian Hudock
I co-advised Brian from 2002-2003. Brad
Bishop in Systems Engineering was his primary Advisor.
Publications
- Bishop, B., Crabbe, F. and Hudock, B., Design of a Low-Cost, Highly
Mobile Urban Search and Rescue Robot. Advanced Robotics, 19(8)
pp. 797--928, 2005.
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Abstract: In this paper, we discuss the design of a novel robotic platform for Urban Search and
Rescue (USAR). The system developed possesses unique mobility capabilities based on a new
adjustable compliance mechanism and overall locomotive morphology. The main facets of this
work involve the morphological concepts, initial design and construction of a prototype vehicle,
and a physical simulation to be used for developing controllers for semi-autonomous (supervisory)
operation. |
- Hudock, B.M., Bishop, B.E. and Crabbe, F.L., On the Development
of a Novel Urban Search and Rescue Robot, in Proceedings of the
Thirty-Sixth Southeastern Symposium on System Theory, March 2004,
pp. 451 - 455
Abstract:
This paper concerns the development of a novel
robotic platform for Urban Search and Rescue (USAR)
efforts. The main facets of this work involve the design
and construction of a new robot morphology and a
physical simulation to be used for developing controllers
for semi-autonomous (supervisory) operation.
- Hudock, B., Development of a Superior Urban
Search-And-Rescue Robot U.S.N.A. Trident Scholar project
report; no. 311 (2003)
Abstract:
The September 11th bombing of the World Trade
Centers in New York illustrated the many problems associated with
rescuing the survivors of a collapsed building. The fact that
survival probability drops dramatically after two days, combined with
the massive amount of debris that needs to be explored, makes the
urban search-and-rescue mission extremely daunting. In addition, the
environment within a pile of debris is very unstable and often too
dangerous for entry by humans. The solution to such a complicated
problem lies in robots capable of quickly exploring a collapsed
building and pinpointing the location of any survivors. My Trident
Scholar project is to build an urban search-and-rescue robot. The
primary goal is to develop a physical structure that will be unique
and versatile enough to traverse different terrain challenges. A
design’s effectiveness will be judged on its ability to overcome
the pre-selected terrain types. The secondary goal is to simplify
operator input by establishing a ‘fly-by-wire’ style controller,
wherein user inputs will be mapped to motor motion commands that will
be developed using a physics simulator. Initially, a simulation model
of the robot needs to be created with responses that closely correlate
to the responses of the actual prototype. Using the simulation,
various methods, including genetic algorithms, will be used to develop
locomotive methods, or ‘gaits,’ for various types of motion,
i.e., lines and curves. The movements will then be translated to the
physical prototype and their effectiveness (the ability to move as
predicted) analyzed. The end result will be a robot with a versatile
mobility controlled using simple operator inputs.
Edward H. L. Fong
Ed was my advisee from 2001-2002, and worked on
robotic mapping of 3-D areas.
Publications:
- Fong, E., Crabbe, Adams, W., Crabbe, F.L., Schultz,
A. C., Representing a 3-D Environment with a 2½-D Map Structure, To
Appear in the proceedings of the International Conference on
Intelligent Robotics and Systems, October 2003.
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Abstract: This paper explores the development of a two and
one-half dimensional (2½-D) map structure to provide an autonomous
mobile robot with a more three-dimensional (3-D) model of its
environment than those afforded by current map structures. The 2½-D
map structure was created by modifying the widely used evidence grid
to store a height, along with a probability value, in each cell
location to record the varying elevations of a 3-D
environment. Results show that this map structure is capable of
providing an autonomous mobile robot with a representation of a
limited 3-D environment that will allow it to perform obstacle
detection, path planning, and to an extent, localization.
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- Fong, E.Acquisition of
3-D Map Structures for Mobile RobotsU.S.N.A. Trident Scholar
project report; no. 295 (2002)
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Abstract: For an autonomous mobile robot to move around
intelligently in its surroundings, it must possess a map of the
environment which it can use to determine where it is, where it wants
to go, and the best way to get there. The ability to successfully
navigate in its surroundings allows the robot to perform more
complicated tasks with greater autonomy. When a mobile robot is
introduced into an unfamiliar environment, it does not have that map
available and therefore must generate one itself. Methods currently
exist to perform such a task in an environment where the robot moves
about a single plane. However, this limitation restricts the robot's
movement to a flat and smooth surface (typically an indoor setting).
This project builds upon current map building techniques to enable a
ground-based mobile robot to navigate robustly in an unfamiliar, more
three-dimensional (outdoor) environment. A new map structure has been
developed to store three-dimensional information in a compressed form.
It represents the robot's environment as a two-dimensional surface
existing in three-dimensional space. This map structure was
implemented on an all-terrain outdoor robot for use in urban
environments. The map structure was tested both by comparing
generated maps to the environment on which they were based, and by
testing the robots ability to navigate with them. The map structure
has been shown to accurately model the robot's environment and enable
the robot to navigate in it while requiring few computational
resources.
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