@TECHREPORT{amc-1992,
AUTHOR = {Jacky Baltes et al.},
TITLE = {Selected student reports from {CPSC} 521, Winter
term 1992},
INSTITUTION = {Alberta Microelectronic Centre},
YEAR = {1992}
}
@TECHREPORT{amc-1993,
AUTHOR = {Jacky Baltes et al.},
TITLE = {Selected student reports from {CPSC} 521, Winter
term 1993},
INSTITUTION = {Alberta Microelectronic Centre},
YEAR = {1993}
}
@TECHREPORT{amc-1994,
AUTHOR = {Jacky Baltes et al.},
TITLE = {Selected student reports from {CPSC} 521, Winter
term 1994},
INSTITUTION = {Alberta Microelectronic Centre},
YEAR = {1994}
}
@INPROCEEDINGS{baltes91,
AUTHOR = {Jacky Baltes},
TITLE = {A symmetric version space algorithm for learning
disjunctive string concepts},
BOOKTITLE = {Proceedings of the fourth University of New
Brunswick Artificial Intelligence Symposium},
YEAR = 1991,
PAGES = {55-65},
MONTH = {September},
URL = {pdf/baltes-1991.pdf},
ABSTRACT = {The symmetric version space algorithm (SVS) learns
disjunctions of string patterns by example. The
learnable string concepts are a subset of regular
expressions. The running time of the algorithm is
{\em reduced}, because the system learns a top--down
description of the string concepts. Different parts
of the algorithm learn descriptions at different
levels of the concept independently. This technique
is similar to factoring the version space, in order
to restrict the search space. The problem of {\em
fragmentation} of the $G$--set is overcome by using
a symmetric version space approach.}
}
@ARTICLE{baltes-1991a,
KEY = {TDS review},
AUTHOR = {Jacky Baltes},
TITLE = {The Transputer Development System},
JOURNAL = {Computing Reviews},
YEAR = {1991},
MONTH = {July},
VOLUME = {32},
NUMBER = {7}
}
@TECHREPORT{baltes91:_integ_plann_repres_macros_abstr_cases,
AUTHOR = {Jacky Baltes and Bruce MacDonald},
TITLE = {An Integrated Planning Representation using Macros,
Abstractions, and Cases},
YEAR = 1991,
MONTH = {December},
INSTITUTION = {University of Calgary}
}
@INPROCEEDINGS{baltes-1992,
AUTHOR = {Jacky Baltes and Bruce MacDonald},
TITLE = {Case--based Meta Learning: Using a Dynamically
Version Space in Sustained Learning},
BOOKTITLE = {Proceedings Ninth Canadian Conference on Artificial
Intelligence},
ORGANIZATION = {Canadian Society for Computational Studies of
Intelligence},
YEAR = {1992},
MONTH = MAY,
EDITOR = {Janice Glasgow and Robert Hadley},
PUBLISHER = {Morgan Kaufman Publishers Inc.},
ADDRESS = {Palo Alto, California},
PAGES = {228-235},
ABSTRACT = {It is well--recognized that in practical inductive
learning systems the search for a concept must be
heavily biased. In addition the bias must be
dynamic, adapting to the current learning
problem. Another important requirement is sustained
learning, allowing transfer from known tasks to new
ones. Previous work on dynamic bias has not
explicitly addressed learning transfer, while
previous case--based learning research suffers from
a variety of problems. This paper presents a method
of Case--Based Meta Learning (CBML), in which the
cases are concepts, rather than instances, and
retrieved similar concepts are used as a skeletal
version space to speed up learning. CBML is
independent of the concept representation
language. The CBML--Clerk system, which learns
repetitive operating system tasks, is presented as a
demonstration.},
URL = {pdf/baltes-1992.pdf}
}
@INPROCEEDINGS{baltes-1992b,
KEY = {ML 92 workshop},
AUTHOR = {Jacky Baltes and Bruce MacDonald},
TITLE = {Case--based Meta Learning: Sustained Learning
supported by a Dynamically Biased Version Space},
BOOKTITLE = {Proceedings of the ML 92 Workshop on Biases in
Inductive Learning},
YEAR = 1992,
MONTH = {July},
EDITOR = {Diana Gordon},
ABSTRACT = {It is well--recognized that in practical inductive
learning systems the search for a concept must be
heavily biased. In addition the bias must be
dynamic, adapting to the current learning
problem. Another important requirement is sustained
learning, allowing transfer from known tasks to new
ones. Previous work on dynamic bias has not
explicitly addressed learning transfer, while
previous case--based learning research suffers from
a variety of problems. This paper presents a method
of Case--Based Meta Learning (CBML), in which the
cases are concepts, rather than instances, and
retrieved similar concepts are used as a skeletal
version space to speed up learning. CBML is
independent of the concept representation
language. The CBML--Clerk system, which learns
repetitive operating system tasks, is presented as a
demonstration.},
URL = {pdf/baltes-1992b.pdf}
}
@INPROCEEDINGS{baltes-1992d,
AUTHOR = {Jacky Baltes and Bruce MacDonald},
TITLE = {An Integrated Planning Representation using Macros,
Abstractions, and Cases},
BOOKTITLE = {Proceedings of the Workshop on Change of
Representation and Problem Reformulation},
YEAR = 1992,
MONTH = APR,
EDITOR = {Michael R. Lowry},
PUBLISHER = {NASA Ames Research Center},
ADDRESS = {Moffet Field, CA 94025,USA},
PAGES = {1-10},
ORGANIZATION = {NASA Ames Research Center},
ABSTRACT = {Planning will be an essential part of future
autonomous robots and integrated intelligent
systems. After giving a brief introduction to the
classical planning paradigm, this paper focuses on
learning problem solving knowledge in planning
systems. A general weak method for learning useful
operators is the creation of macros. The paper first
describes a novel approach to the selection and
dynamic filtering of macros. The dynamic filtering
approach is suggested for controlling the creation
of operators. A new planning representation is
proposed that uses a common representation for
macros, abstractions, and cases. A general operator
is represented by sequences of primitive or
non--primitive operators. A macro is equivalent to a
sequence of primitive, executable, operators with
uninstantiated arguments. A case consists of
primitive operators with instantiated arguments. An
abstract plan is equivalent to a sequence of
non--primitive operators at a lower level of
abstraction. A learned indexing mechanism allows
rapid access to relevant operators. The system is
able to use both classical and case--based
techniques. The general operators in a successful
plan derivation would be assessed for the potential
usefulness, and some stored.},
URL = {pdf/baltes-1992d.pdf}
}
@INPROCEEDINGS{baltes-1992e,
KEY = {ML workshop at CAI 92},
AUTHOR = {Bruce MacDonald and Jacky Baltes},
TITLE = {Research in instructable Systems},
BOOKTITLE = {Machine Learning Workshop at AI/GI/VI '92},
YEAR = {1992},
MONTH = {May}
}
@TECHREPORT{baltes-1992f,
KEY = {Tech report of string paper},
AUTHOR = {Jacky Baltes},
TITLE = {Symmetric Version Space Algorithm for Learning
Disjunctive String Concepts},
INSTITUTION = {University of Calgary},
YEAR = {1992},
MONTH = {March},
ADDRESS = {Calgary,Alta},
NUMBER = {92/469/06},
URL = {pdf/baltes-1992f.pdf}
}
@PHDTHESIS{baltes-1996,
AUTHOR = {Jacky Baltes},
TITLE = {DoLittle: a learning multi-strategy planning system},
SCHOOL = {University of Calgary},
YEAR = 1996,
MONTH = {June},
ABSTRACT = {Multi-strategy planning focuses on the selection and
combination of different problem solving
methods. Since planning is intractable in complex
domains, researchers have developed different
methods to restrict, restructure, or reorder the
search space and to search the new space. These
reformulations of the search space are based on
assumptions about the domain or other features of
the task such as the problem order, plan structure,
or subgoal hierarchy. These planners, then, work
well in domains where the underlying assumptions are
met, and fail otherwise. Furthermore, in complex
domains it is possible that only parts of a task can
be efficiently solved with a given planning
method. But for other parts of the tasks, a
different planning strategy may be appropriate. The
goal of multi-strategy planning is to alleviate this
problem by selecting and combining different problem
solving methods on a single problem. First, planning
is seen as search through the space of partial
plans. Different planning strategies can be
described by the language of partial plans, the set
of transformations on partial plans, and the search
method. Secondly, the thesis develops a theory of
multi-strategy planning and shows that a
multi-strategy planner can exponentially improve
performance over a single strategy planner and
derives sufficient conditions for this
improvement. Thirdly, the thesis proposes
\emph{general operators} (\Strips\ operators with
added refinements) as a representation for different
planning strategies and shows how general operators
can represent different planning methods. Fourthly,
the thesis develops a search control method that,
given a planning method expressed as a general
operator reduces the associated search space
similarly to the original problem solving
strategy. % The search strategy is based on a
cheapest first method. Based on % the assumption
that all planning strategies have similar reduction
% probabilities, the planning strategy with the
smallest refinement % cost is selected. Since the
generation of general operators may be cumbersome by
hand, and since the system is intended as a part of
a learning apprentice system, \DoLittle\ learns new
general operators from examples. The planning bias
learners are highly specific methods that have
knowledge of \DoLittle's operator set and search
method and create new general operators to exploit a
given planning bias. Through an empirical
evaluation, this research shows (a) that
multi-strategy planning improves the performance
over single strategy planning in some toy domains,
(b) that multi-strategy planning can solve problems
in at least one complex domain (the kitchen domain),
and (c) and that an unordered subproblem coordinated
multi-strategy planner performs better in the
kitchen domain than a problem coordinated one. },
URL = {pdf/baltes-1996.pdf}
}
@INPROCEEDINGS{baltes-1997,
AUTHOR = {Jacky Baltes},
TITLE = {DoLittle: A Multi-strategy planning system},
BOOKTITLE = {Proceedings of the IASTED International Conference
on Artificial Intelligence and Soft Computing},
EDITOR = {M.H. Hamza},
YEAR = 1997,
ORGANIZATION = {IASTED},
PUBLISHER = {IASTED Acta Press},
MONTH = {July},
PAGES = {435-439},
ABSTRACT = {This paper introduces multi-strategy planning, which
focuses on the selection and combination of
different planning methods. Planning is the problem
of finding a sequence of actions (operators) that
will take an agent from one state (initial state) to
a desired state (goal). This problem has gotten
considerable attention in artificial
intelligence. Unfortunately, theoretical results
show that the general planning problem is
intractable in complex domains. Therefore, a
practical planning system reduce the search
space. This reduction of the search space is based
on assumptions (so called \emph{planning biases\/})
about the problem such as: the problem order, plan
structure, or subgoal hierarchy. Given these
assumptions about the task, a \emph{planning
strategy\/} exploits the reduction in the search
space and searches the resulting search
space. Popular examples of planning strategies are
means-ends analysis, case-based planning,
macro-operators, abstraction hierarchies, and
non-linear planning. Planning strategies based on a
specific planning bias work well in domains, in
which these assumptions are satisfied, but fail if
these assumptions are not met. Furthermore, in
complex domains it is possible that only parts of a
task can be efficiently solved with a given planning
method. But for other parts of the tasks, a
different planning strategy may be appropriate.},
URL = {pdf/baltes-1997.pdf}
}
@INPROCEEDINGS{baltes-1998,
AUTHOR = {Jacky Baltes and Nicholas Hildreth and Yuming Lin},
TITLE = {The All Botz RoboCup Team},
BOOKTITLE = {Proceedings of the PRICAI Workshop on RoboCup},
YEAR = 1998,
ADDRESS = {Singapore},
MONTH = {November},
URL = {pdf/baltes-1998.pdf}
}
@INPROCEEDINGS{baltes00:_adapt_path_plann_system_highl_dynam_envir,
AUTHOR = {Jacky Baltes and Nicholas Hildreth},
TITLE = {Adaptive Path Planning System for Highly Dynamic
Environments},
BOOKTITLE = {Proceedings of ICARCV},
YEAR = 2000,
ANNOTE = {Description of our adaptive path planner}
}
@INPROCEEDINGS{baltes00:_all_botz,
AUTHOR = {Jacky Baltes and Nicholas Hildreth and David
Maplesdon},
TITLE = {All Botz},
BOOKTITLE = {RoboCup-99: Robot Soccer World Cup III},
PAGES = {653-656},
YEAR = 2000,
EDITOR = {Manuela Veloso and Enrico Pagello and Hiroaki
Kitano},
ADDRESS = {New York},
PUBLISHER = {Springer},
ANNOTE = {Description of our RoboCup Team},
ISBN = {ISBN-3-540-41043-0},
ABSTRACT = {This paper discusses some important features, which
make the All Botz, the University of RoboCup team, a
very unique team. In particular, the use of cheap
hardware and the design of the video server. },
URL = {pdf/robocup99-3.pdf}
}
@INPROCEEDINGS{baltes00:_bench_suite_mobil_robot,
AUTHOR = {Jacky Baltes},
TITLE = {A Benchmark Suite for Mobile Robots},
BOOKTITLE = {Proceedings of IROS-2000},
YEAR = 2000,
MONTH = {November},
ORGANIZATION = {IEEE},
ABSTRACT = {This paper describes a benchmark suite for mobile
robots that provides quantitative measurements of a
mobile robot's ability to perform specific
tasks. Guidelines for the design of benchmark tests
were derived from other areas faced with the problem
of evaluating complex systems. The benchmarks test
the control and accuracy of the path and trajectory
tracking, the static path planning, and the dynamic
path planning ability of a mobile robot. A set of
metrics that provide important information about a
mobile robot's performance are also presented. These
benchmarks could also be used as simple games. Their
inclusion in robotic games will lead to an increased
opportunity fo researchers to evaluate their work
without having to buy expensive or special purpose
equipment.},
URL = {pdf/baltes00:_bench_suite_mobil_robot.pdf},
SLIDES = {pdf/baltes00:_bench_suite_mobil_robot_slides.pdf}
}
@INPROCEEDINGS{baltes00:_path_contr_non_car_robot,
AUTHOR = {Jacky Baltes and Yuming Lin},
TITLE = {Path-tracking Control of Non-holonomic Car-like
Robots Using Reinforcement Learning},
BOOKTITLE = {RoboCup-99: Robot Soccer World Cup III},
PAGES = {162-173},
YEAR = 2000,
EDITOR = {Manuela Veloso and Enrico Pagello and Hiroaki
Kitano},
ADDRESS = {New York},
PUBLISHER = {Springer},
ANNOTE = {Description of Yuming's MSc thesis work. A
reinforcement learning controller using a case based
reasoning system to deal with a a continuous control
space},
ISBN = {ISBN-3-540-41043-0},
ABSTRACT = {This paper investigates the use of reinforcement
learning in solving the path-tracking problem for
car-like robots. The reinforcement learner uses a
case-based function approximator, to extend the
standard reinforcement learning paradigm to handle
continuous states. The learned controller performs
comparable to the best traditional control functions
in both simulation and also in practical driving. },
URL = {pdf/baltes00:_path_contr_non_car_robot.pdf}
}
@INPROCEEDINGS{baltes00:_pract_camer_colour_calib_large_rooms,
AUTHOR = {Jacky Baltes},
TITLE = {Practical Camera and Colour Calibration for Large
Rooms},
BOOKTITLE = {RoboCup-99: Robot Soccer World Cup III},
PAGES = {148-161},
YEAR = 2000,
EDITOR = {Manuela Veloso and Enrico Pagello and Hiroaki
Kitano},
ADDRESS = {New York},
PUBLISHER = {Springer Verlag},
ANNOTE = {Description of our camera and colour calibration},
ISBN = {ISBN-3-540-41043-0},
ABSTRACT = {This paper describes a practical method for
calibrating the geometry and colour information for
cameras surveying large rooms. To calibrate the
geometry, we use a semi-automatic system to assign
real world to pixel coordinates. This information is
the input to the Tsai camera calibration method. Our
system uses a two stage process in which easily
recognizable objects (squares) are used to sort the
individual data points and to find missing
objects. Fine object features (corners) are used in
a second step to determine the object's real world
coordinates. An empirical evaluation of the system
shows that the average and maximum errors are
sufficiently small for our domain. Objects are
recognized through coloured spots. The colour
calibration uses six thresholds (Three colour ranges
(Red, Green, and Blue) and three colour differences
(Red - Green, Red - Blue, Green - Blue)). This paper
describes a fast threshold comparison routine. },
URL = {pdf/baltes00:_pract_camer_colour_calib_large_rooms.pdf},
SLIDES = {pdf/baltes00:_pract_camer_colour_calib_large_rooms_slides.pdf}
}
@INPROCEEDINGS{baltes00:_subsum_based_contr_mobil_robot_dynam_envir,
AUTHOR = {Jacky Baltes},
TITLE = {Subsumption-Based Control for Mobile Robots in
Dynamic Environments},
BOOKTITLE = {Proceedings of ICARCV},
YEAR = 2000,
ANNOTE = {Description of our controller for 2000. Mainly based
on a Ben's work},
ABSTRACT = {This paper describes an architecture for path
planning and control of car-like mobile robots. The
method is based on a subsumption architecture with
four individual behaviors: approach, steer, turn,
and progress. The coordination of these simple
behaviors results in a robust control architecture
for mobile robots that performed well when compared
to other control methods. The controller also
results in simplifying the requirements on the path
planner.},
URL = {pdf/baltes00:_subsum_based_contr_mobil_robot_dynam_envir.pdf},
SLIDES = {pdf/baltes00:_subsum_based_contr_mobil_robot_dynam_envir_slides.pdf}
}
@INCOLLECTION{baltes01:_adapt_path_plann_highl_dynam_envir,
TITLE = {Adaptive Path Planner for Highly Dynamic Environments},
AUTHOR = {Jacky Baltes and Nicholas Hildreth},
BOOKTITLE = {{R}obo{C}up-2000: Robot Soccer World Cup {IV}},
EDITOR = {Peter Stone and Tucker Balch and Gerhard Kraetszchmar},
PUBLISHER = {Springer Verlag},
ADDRESS = {Berlin},
YEAR = 2001,
PAGES = {76--85},
ABSTRACT = {This paper describes adaptive path planning, a novel
approach to path planning for car-like mobile
robots. Instead of creating a new plan from scratch,
whenever changes in the environment invalidate the
current plan, the adaptive path planner attempts to
adapt the old plan to the new situation. The paper
proposes an efficient representation for path that
is easily amendable to adaptation. Associated with
the path planner is a set of repair
strategies. These repair strategies are local
methods to fix a plan to compensate for object
movement in the domain. The repair strategies are
specific and have a high probability of being able
to fix a plan. An empirical evaluation shows that
adaptive path planning is suitable to highly dynamic
domains, such as \RoboCup. Adaptive path planning
reduces the cumulative planning time by a factor of
$2.7$ compared to Bicchi's planner. At the same
time, the quality of the plans generated by the
adaptive path planner were similar to those
generated by Bicchi's planner.},
URL = {pdf/baltes01:_adapt_path_plann_highl_dynam_envir.pdf},
SLIDES = {pdf/baltes01:_adapt_path_plann_highl_dynam_envir_slides.pdf}
}
@INPROCEEDINGS{baltes01:_camer_calib_rectan_textur,
AUTHOR = {Jacky Baltes},
TITLE = {Camera Calibration of Rectangular Textures},
BOOKTITLE = {Proceedings of the Robot Vision Workshop},
YEAR = 2001,
ADDRESS = {Auckland, New Zealand},
MONTH = {February},
ORGANIZATION = {Centre for Imaging Technology and Robotics},
ANNOTE = {Description of application of our matching points
algorithm to calibration of rectangular patterns},
ABSTRACT = {This paper describes a practical method for the
camera calibration given a single image of a regular
texture. This paper uses the calibration of images
of skyscrapers as an example. The paper introduces
two algorithms for the assignment of real world
coordinates to feature points. The first algorithm
selects five closely connected feature points and
determines the orientation of the rectangular
pattern. The second algorithm iteratively sorts the
feature points and assigns real world coordinates to
them. Lastly, the Tsai camera calibration algorithm
is used to compute the camera parameters. },
URL = {pdf/baltes01:_camer_calib_rectan_textur.pdf},
SLIDES = {pdf/baltes01:_camer_calib_rectan_textur_slides.pdf}
}
@INPROCEEDINGS{baltes01:_horus,
AUTHOR = {Jacky Baltes},
TITLE = {Horus: Object Orientation and ID Without Additional
Markers},
BOOKTITLE = {Proceedings of the Robot Vision Workshop},
YEAR = 2001,
MONTH = {February},
ADDRESS = {Auckland, New Zealand},
ABSTRACT = {This paper describes a novel approach to detecting
orientation and identity of robots using a global
vision system. Instead of additional markers, the
original shape of the robot is used to determine an
orientation using a general Hough transform. In
addition the movement history as well as the command
history are used to calculate the quadrant of the
orientation as well as the identity of the robot. An
empirical evaluation shows that the performance of
the new video server is at least as good as that of
a traditional approach using additional coloured
markers. },
URL = {pdf/baltes01:_horus.pdf},
SLIDES = {pdf/baltes01:_horus_slides.pdf}
}
@INPROCEEDINGS{baltes01:_roboc,
AUTHOR = {Jacky Baltes and Nicholas Hildreth},
TITLE = {RoboCup99: A Student's Perspective},
BOOKTITLE = {Proceedings of the Robot Vision Workshop},
YEAR = 2001,
MONTH = {February},
ABSTRACT = {One of the reasons for organizing robotic games is
that they allow researchers to evaluate their
systems and approaches on a level playing
field. This evaluation is important in a quickly
developing field such as robotics with few real
world applications. This paper investigates through
a case-study how much participating at the
RoboCup-99 competition has benefited a MSc. student
at the University of Auckland. Although the
participation was certainly stimulating, its
influence on the research was indirect. The paper
makes a number of suggestions that will make it
easier to quantitatively evaluate research at these
competitions and thus influence research more
directly.},
URL = {pdf/baltes01:_roboc.pdf},
SLIDES = {pdf/baltes01:_roboc_slides.pdf}
}
@INPROCEEDINGS{baltes94:_distr_archit_instr_probl_solver,
AUTHOR = {Jacky Baltes and Bruce MacDonald},
TITLE = {A Distributed Architecture for an Instructable
Problem Solver},
BOOKTITLE = {Proceedings of the Twenty-Seventh Annual Hawaii
Conference on System Sciences},
PAGES = {63-73},
YEAR = 1994,
VOLUME = 3,
ADDRESS = {Wailaea, Hawaii},
MONTH = {January},
ABSTRACT = {Our research goal is to design systems that enable
humans to teach tedious, repetitive, simple tasks to
a computer. We propose here a learner/problem solver
architecture for such a system. The problem solving
module is able to combine diverse problem solving
strategies on a single problem, by using a common
representation for operators, and learning operators
by analyzing solution traces. At the distributed
processor level, the design provides a general
dynamic load balancing system that has little domain
knowledge. It is controlled from the next level by a
tightly constrained planner. The distributed problem
solver testbed enables us to design, experiment
with, and evaluate our combined learning/problem
solving system for automating users' repetitive
tasks.},
URL = {pdf/baltes94:_distr_archit_instr_probl_solver.pdf}
}
@INPROCEEDINGS{baltes94:_evolut_digit_logic_lab,
AUTHOR = {Jacky Baltes and Cameron Patterson},
TITLE = {The Evolution of a Digital Logic Lab},
BOOKTITLE = {Proceedings of the 1994 Canadian Workshop on Field
Programmable Devices},
PAGES = {Section 3.5.1},
YEAR = 1994,
ADDRESS = {Kingston, Ontario},
MONTH = {June},
ABSTRACT = {This paper describes different technologies that
were used in a VLSI design course at the university
of Calgary. The main goal of this paper is to show
how the advent of new technology allows students to
spend more time on design capture, logic simulation,
and the design of test vectors, as opposed to the
tedious tasks of implementing/fabricating a design
and a test environment. This trend has lead to more
and more complex and interesting projects. In recent
years, the students used VHDL to create a behavioral
description of their circuit and synthesize a
schematic from it. The synthesis targets Actel or
Xilinx FPGAs. The example project is the design of a
GCD circuit, which the authors selected because of a
number of desirable characteristics: most
importantly, (a) it is complex enough to allow the
students freedom in their design, and (b) it can
easily be adapted to the available hardware
resources. The paper includes a small example of the
conversion from an algorithm into a finite state
machines, one of the crucial steps in the design
phase. In the future, we hope to use configurable
hardware (the Algotronix \CHS) with a powerful
connection to a host computer. This will allow
students even greater flexibility in their design,
since they can choose which parts are implemented in
hardware and which are done through software.},
URL = {pdf/baltes94:_evolut_digit_logic_lab.pdf}
}
@ARTICLE{baltes95:_trans_hardw_system_desig,
AUTHOR = {Jacky Baltes},
TITLE = {Transputer Hardware and System Design},
JOURNAL = {Computing Reviews},
YEAR = 1995,
MONTH = FEB,
VOLUME = 36,
NUMBER = 2,
ABSTRACT = {The reviewed book is intended as a practical guide
to transputer hardware design. The authors do not
assume prior knowledge of the transputer
architecture, but the reader should be familiar with
more conventional micro-processor design.},
URL = {compreview95-1.pdf}
}
@INPROCEEDINGS{baltes98:_plann_strat_repres_dolit,
AUTHOR = {Jacky Baltes},
TITLE = {Planning Strategy Representation in DoLittle},
BOOKTITLE = {Advances in Artificial Intelligence},
PAGES = {30-44},
YEAR = 1998,
PUBLISHER = {Springer},
ABSTRACT = {This paper introduces multi-strategy planning and
describes its implementation in the \DoLittle\
system, which can combine many different planning
strategies, including means-ends analysis,
macro-based planning, abstraction-based planning
(reduced and relaxed), and case-based planning on a
single problem. \emph{Planning strategies} are
defined as methods to reduce the search space by
exploiting some assumptions (so-called
\emph{planning biases}) about the problem
domain. \emph{General operators} are generalizations
of standard \Strips\ operators that conveniently
represent many different planning strategies. The
focus of this work is to develop a representation
weak enough to represent a wide variety of different
strategies, but still strong enough to emulate
them. The search control method applies different
general operators based on a strongest first
principle; planning biases that are expected to lead
to small search spaces are tried first. An empirical
evaluation in three domains showed that
multi-strategy planning performed significantly
better than the best single strategy planners in
these domains.},
URL = {pdf/baltes98:_plann_strat_repres_dolit.pdf}
}
@INPROCEEDINGS{baltes98:_pract_camer_calib_large_rooms,
AUTHOR = {Jacky Baltes},
TITLE = {Practical Camera Calibration for Large Rooms},
BOOKTITLE = {Proceedings of the Image and Vision Conference},
YEAR = 1998,
MONTH = {December},
ABSTRACT = {This paper describes our practical experiences and
methods for calibrating a large room. We show a
semi-automatic system to assign real world
coordinates to image features. Our system uses a two
stage process in which easily recognizable objects
(squares) are used to sort the individual data and
to find missing objects. Fine object features
(corners) are used in a second step to determine the
image real world coordinates. An empirical
evaluation of the system shows that the average and
maximum errors are sufficiently small for our
problem domain (autonomous mobile agents playing
soccer)},
URL = {pdf/baltes98:_pract_camer_calib_large_rooms.pdf},
SLIDES = {pdf/baltes98:_pract_camer_calib_large_rooms_slides.pdf}
}
@INPROCEEDINGS{baltes99:_fuzzy_logic_contr_car_like_mobil_robot,
AUTHOR = {Jacky Baltes and Robin Otte},
TITLE = {A Fuzzy Logic Controller for Car-Like Mobile Robots},
BOOKTITLE = {Prcoeedings of the International Symposium on
Computational Intelligence in Robotics and
Automation},
YEAR = 1999,
ADDRESS = {Monterey, CA},
MONTH = {November},
ORGANIZATION = {IEEE},
ANNOTE = {Description of the fuzzy logic controller for our
toy cars.},
ABSTRACT = {This paper describes a fuzzy logic controller for
car-like mobile robots. It also introduces a simple
heuristic that helps a designer in the specification
of fuzzy input and output sets. The design of fuzzy
rules follows intuitively from the design of the
fuzzy input sets. In practical tests, this Fuzzy
Logic controller resulted in greatly reduced errors
and also resulted in a control law with 75\% less
control work than a traditional sliding mode
controller.},
URL = {pdf/baltes99:_fuzzy_logic_contr_car_like_mobil_robot.pdf}
}
@INPROCEEDINGS{baltes99:_path_contr_non_car_robot,
AUTHOR = {Jacky Baltes and Yuming Lin},
TITLE = {Path-tracking Control of Non-holonomic Car-like
Robots Using Reinforcement Learning},
BOOKTITLE = {Proceedings of the IJCAI Workshop on RoboCup},
YEAR = 1999,
ADDRESS = {Stockholm, Sweden},
MONTH = {July}
}
@INPROCEEDINGS{baltes99:_pract_camer_colour_calib_large_scale_rooms,
AUTHOR = {Jacky Baltes},
TITLE = {Practical Camera Calibration for Large Rooms},
BOOKTITLE = {RoboCup '99},
YEAR = 1999,
ADDRESS = {Stockholm, Sweden},
MONTH = {July}
}
@INPROCEEDINGS{baltes99:_all_botz,
AUTHOR = {Jacky Baltes and Nich Hildreth and David Maplesdon},
TITLE = {The All Botz RoboCup Team},
BOOKTITLE = {RoboCup '99},
YEAR = 1999,
ADDRESS = {Stockholm, Sweden},
MONTH = {July}
}
@INPROCEEDINGS{lin99:_micro_contr_board_suppor_intel,
AUTHOR = {XinKe Lin and Jacky Baltes},
TITLE = {Micro-Controller Board to Support Intelligent
Control of Car-Like Mobile Robots},
BOOKTITLE = {Proceedings of ENZCON-99},
YEAR = 1999,
ADDRESS = {Auckland, New Zealand},
MONTH = {November},
ABSTRACT = {This paper describes the design and implementation
of an embedded system for the low level control of
autonomous mobile robots. The micro controller board
provides more accurate speed and direction control,
more reliable digital communication, and facilities
for additional sensors and actuators. The velocity
control is implemented by a one bit D-A converter
using pulse width modulation. The data rate of the
digital communication is limited to five Bytes/sec.,
which is sufficient for simple navigation tasks. },
URL = {pdf/lin99:_micro_contr_board_suppor_intel.pdf}
}
@INPROCEEDINGS{lin99:_path_contr_non_car_robot_reinf_learn,
AUTHOR = {Yuming Lin and Jacky Baltes},
TITLE = {Path-tracking Control of Non-holonomic Car-like
Robots with Reinforcement Learning},
BOOKTITLE = {Computer Science Research Students's Conference},
PAGES = {6-13},
YEAR = 1999,
ADDRESS = {Hamilton, New Zealand},
MONTH = {April}
}
@INPROCEEDINGS{noonan98:_pc_inter_remot_contr_car,
AUTHOR = {Ben Noonan and Jacky Baltes and Bruce MacDonald.},
TITLE = {PC Interface for a Remote Controlled Car},
BOOKTITLE = {Proceedings of the IPENZ sustainable city
conference},
PAGES = {22-27},
YEAR = 1998,
ADDRESS = {Auckland, New Zealand},
MONTH = {February},
ABSTRACT = {This paper discusses the design of an interface for
a PC and a commercially available remote-controlled
car. The objective of the project is to provide the
capability for a PC to emulate a conventional RC
transmitter. The micro-controller-based design
provides the best means of extendibility and
flexibility where future requirements are yet to be
defined, it also significantly reduces the
processing requirements on the host PC and the
client application. The data communications between
the host PC and the interface is via a standard
parallel port implementation that provides a
platform independent communications medium. The
firmware design is based on a single, restart-able
task paradigm with interrupts for communications and
other system functions. This is motivated by a need
for quick execution of commands by the interface. An
active braking application was used to evaluate
advanced functionality, which produced encouraging
results, and showed superior control compared with
the original manual controller. A client application
was written to test the functionality of the
interface and data communications.},
URL = {pdf/noonan98:_pc_inter_remot_contr_car.pdf},
SLIDES = {pdf/noonan98:_pc_inter_remot_contr_car_slides.pdf}
}
@INPROCEEDINGS{xu99:_paral_port_inter_mentor_robot_arm,
AUTHOR = {Weidong Xu and Jacky Baltes},
TITLE = {Parallel Port for Interface for the Mentor Robot
Arm},
BOOKTITLE = {Proceedings of ENZCON-99},
YEAR = 1999,
ADDRESS = {Auckland, New Zealand},
MONTH = {November},
ANNOTE = {Description of parallel port interface board},
ABSTRACT = {This paper describes the design of an interface
board which by emulating the bus of some popular
home computers can control legacy hardware through a
generic parallel port interface and serial
interface. In particular, the board is currently
being used to control two Mentor robot arms from a
PC. We also developed firmware and a device driver
for the Linux operating system.},
URL = {pdf/xu99:_paral_port_inter_mentor_robot_arm.pdf}
}
@INPROCEEDINGS{zhou00:_ferret,
AUTHOR = {Yuhua Zhou and Jacky Baltes},
TITLE = {Ferret: An Intelligent Assistant for Internet
Searching},
BOOKTITLE = {Proceedings of the Pacific Rim Conference on AI},
YEAR = 2000,
ABSTRACT = {This paper describes the design and implementation
of Ferret, an information-seeking assistant that
helps a user find information on the World Wide
Web. It analyzes and automatically clusters the
returned pages from a search engine.},
URL = {pdf/zhou00:_ferret.pdf}
}
@MISC{baltes01:_toy_elect,
AUTHOR = {Jacky Baltes},
TITLE = {Toy Electronics},
NOTE = {Invited tutorial at the conference for Artificial
Intelligence and Soft Computing},
MONTH = {May},
YEAR = 2001,
ABSTRACT = {The tutorial describes the initial steps in the
development of a robotic platform that can be used
for many experiments into AI. The system uses remote
controlled cars as platforms and is thus inexpensive
and easily available. A standard framegrabber and
video camera are used to provide vision information
to the processor. The tutorial will lesson the
learning curve for people by describing efficient
methods for image processing and control. This
methods have been developed by the All Botz in the
previous years and have proven their effectiveness
in many games and demonstrations. Effectively, this
will provide participants with solutions to the low
level problems associated with soccer playing
robots. Therefore, the participants of the tutorial
will be able to build their own team in short time
and to use it to test higher level AI and Soft
Computing methods.},
URL = {pdf/baltes01:_toy_elect.tar.gz}
}
@MISC{baltes99:_time_manag_graduat_studen,
AUTHOR = {Jacky Baltes},
TITLE = {Time Management for Graduate Students},
HOWPUBLISHED = {Invited Talk at the New Zealand Graduate Student
Conference for Computer Science},
MONTH = {April},
YEAR = 1999,
SLIDES = {pdf/baltes99:_time_manag_graduat_studen_slides.pdf}
}
@MISC{baltes00:_pract_camer_calib_objec_track,
AUTHOR = {Jacky Baltes},
TITLE = {Practical Camera Calibratio and Object Tracking},
HOWPUBLISHED = {Invited Talk at the National University of
Singapore, Singapore},
MONTH = {February},
YEAR = 2000,
SLIDES = {pdf/baltes00:_pract_camer_calib_objec_track_slides.pdf}
}
@MISC{baltes00:_robot_soccer_multi_agent_resear_tool,
AUTHOR = {Jacky Baltes},
TITLE = {Robotic Soccer as Multi-Agent Research Tool},
HOWPUBLISHED = {Keynote Address at the Workshop on Multiagent Systems},
MONTH = {December},
YEAR = 2000,
NOTE = {Massey Univeristy, Auckland, New Zealand},
SLIDES = {pdf/baltes00:_robot_soccer_multi_agent_resear_tool_slides.pdf}
}
@MISC{baltes99:_use_linux_comput_scien_educat,
AUTHOR = {Jacky Baltes},
TITLE = {Use of Linux in Computer Science Education},
HOWPUBLISHED = {Invited Talk at the IEEE New Zealand Meeting},
MONTH = {September},
YEAR = 1999,
SLIDES = {pdf/baltes99:_use_linux_comput_scien_educat_slides.pdf}
}
@MISC{baltes99:_stoog_homep,
AUTHOR = {Jacky Baltes},
TITLE = {The 4 Stooges Homepage},
HOWPUBLISHED = {WWW},
MONTH = {November},
YEAR = 1999,
NOTE = {http://www.citr.auckland.ac.nz/\~{ }jacky},
ANNOTE = {Homepage of the four stooges.}
}
@INPROCEEDINGS{baltes02:_compar_sever_machin_learn_techn,
AUTHOR = {Jacky Baltes and Yong Joo Park},
TITLE = {Comparison of Several Machine Learning Techniques in
Pursuit-Evasion Games},
BOOKTITLE = {RoboCup-01: Robot Soccer World Cup V},
YEAR = 2002,
ADDRESS = {New York},
PUBLISHER = {Springer},
ABSTRACT = {This paper describes the results of an empirical
evaluation comparing the performance of five
different algorithms in a pursuit and evasion
game. The pursuit and evasion game was played using
two robots. The task of the pursuer was to catch the
other robot (the evader). The algorithms tested were
a random player, the optimal player, a genetic
algorithm learner, a k-nearest neighbor learner, and
a reinforcement learner. The k-nearest neighbor
learner performed best overall, but a closer
analysis of the results showed that the genetic
algorithm suffered from an exploration-exploitation problem.},
URL = {pdf/baltes02:_compar_sever_machin_learn_techn.pdf}
}
@INPROCEEDINGS{baltes02:_effic_image_proces_increas_resol,
AUTHOR = {Jacky Baltes},
TITLE = {Efficient Image Processing for Increased Resolution
and Color Correctness of CMOS Image Sensors},
BOOKTITLE = {RoboCup-01: Robot Soccer World Cup V},
YEAR = 2002,
PUBLISHER = {Springer},
ABSTRACT = {This paper describes fast demosaicing methods to
quadruple the resolution of a CMOS camera. The
resulting increase in accuracy in camera calibration
and object detection is important for local vision
robots, especially those that use computer vision as
their only source of information about the state of
the world. The paper describes two methods for
demosaicing: interpolation and variance
demosaicing. A comparison of three sample views is
shown to demonstrate the increased resolution and
the difference between the interpolation and
variance demosaicing methods. Both demosaicing
methods work well. Variance demosaicing performs
better around edges in the image, but is
computationally more expensive.},
URL = {pdf/baltes02:_effic_image_proces_increas_resol.pdf}
}
@INPROCEEDINGS{baltes02:_yuefei,
AUTHOR = {Jacky Baltes},
TITLE = {YueFei: Object Orientation and Id without Additional Markers},
BOOKTITLE = {RoboCup-01: Robot Soccer World Cup V},
YEAR = 2002,
ADDRESS = {New York},
PUBLISHER = {Springer},
URL = {pdf/baltes02:_yuefei.pdf},
ABSTRACT = {This paper describes a novel approach to detecting
orientation and identity of robots using a global
vision system. Instead of additional markers, the
shape of the robot is used to determine an
orientation using a general Hough transform. In
addition the movement history as well as the command
history are used to calculate the quadrant of the
orientation. The identity of the robot is determined
by correlating the motion of the robot with the
command history. An empirical evaluation shows that
the performance of the new video server is at least
as good as that of a traditional approach using
additional coloured markers.}
}
@INCOLLECTION{baltes4stooges,
AUTHOR = {Jacky Baltes},
TITLE = {4 Stooges},
BOOKTITLE = {RoboCup 2001: Robot Soccer World Cup V},
PUBLISHER = {Springer-Verlag},
YEAR = 2002,
EDITOR = {A. Birk and S. Coradeschi and S. Tadokoro},
VOLUME = 2377,
SERIES = {Lecture Notes on AI},
PAGES = {559-562},
ADDRESS = {Berlin}
}
@INPROCEEDINGS{baltes02:_effic_local_mobil_robot,
AUTHOR = {Jacky Baltes},
TITLE = {Efficient Localization for Mobile Robots},
BOOKTITLE = {Proceedings of the 2002 FIRA World Congress},
YEAR = 2002,
ORGANIZATION = {Federation of International Robot-soccer Association}
}
@INPROCEEDINGS{baltes02:_devel_walkin_gaits_small_human_robot,
AUTHOR = {Jacky Baltes and Patrick Lam},
TITLE = {Development of Walking Gaits for a Small Humanoid Robot},
BOOKTITLE = {Proceedings of the 2002 FIRA World Congress},
YEAR = 2002,
ORGANIZATION = {Federation of International Robot-soccer Association}
}
@INPROCEEDINGS{baltes02:_local_mobil_robot_using_lines,
AUTHOR = {Jacky Baltes},
TITLE = {Localization for Mobile Robots Using Lines},
BOOKTITLE = {Proceedings of the Seventh International Conference
on Control, Automation, Robotics and Vision
(ICARCV)},
YEAR = 2002,
MONTH = {December}
}
@INPROCEEDINGS{baltes02:_strat_selec_goal_gener_role,
AUTHOR = {Jacky Baltes},
TITLE = {Strategy Selection, Goal Generation, and Role
Assignment in a Robotic Soccer Team},
BOOKTITLE = {Proceedings of the Seventh International Conference
on Control, Automation, Robotics and Vision
(ICARCV)},
YEAR = 2002
}
@INPROCEEDINGS{lam02:_devel_walkin_gaits_small_human_robot,
AUTHOR = {Patrick Lam and Jacky Baltes},
TITLE = {Development of Walking Gaits for a Small Humanoid Robot},
BOOKTITLE = {Proceedings of the International Conference on
Artificial Intelligence and Soft Computing},
YEAR = 2002,
ORGANIZATION = {IASTED},
PUBLISHER = {Acta Press}
}
@INPROCEEDINGS{baltes02:_pragm_approac_robot_rescue,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {A Pragmatic Approach to Robot Rescue: The Keystone
Fire Brigade},
BOOKTITLE = {AAAI Mobile Robot Competition},
PAGES = {38-43},
YEAR = 2002,
EDITOR = {William D. Smart and Tucker R. Balch and Holly A. Yanco},
VOLUME = {WS-02-18},
SERIES = {AAAI Technical Report},
PUBLISHER = {AAAI Press},
ISBN = {1-57735-176-2}
}
@INPROCEEDINGS{baltes02:_doraem,
AUTHOR = {Jacky Baltes},
TITLE = {Doraemon: Object Orientation and Id without Additional Markers},
BOOKTITLE = {2nd IFAC Conference on Mechatronic Systems},
YEAR = {2002},
MONTH = {December},
ORGANIZATION = {American Automatic Control Council}
}
@INBOOK{braunl03:_embed_robot,
AUTHOR = {Thomas Braunl},
TITLE = {Embedded Robotics},
CHAPTER = {Camera Interface},
PUBLISHER = {Springer Verlag},
YEAR = 2003,
ADDRESS = {Heidelberg}
}
@INPROCEEDINGS{wasalathantra98:_mobil_robot_probl_solver,
AUTHOR = {Sanj Wasalathantra and Bruce MacDonald and Jacky Baltes},
TITLE = {Mobile Robot Problem Solver},
BOOKTITLE = {Proceedings of the IPENZ Sustainable City Conference},
YEAR = 1998,
ADDRESS = {Auckland, New Zealand}
}
@INPROCEEDINGS{macdonald95,
AUTHOR = {Bruce MacDonald and Jacky Baltes and Istavan Hernadi},
TITLE = {An architecture for understanding human instruction, planning, and learning},
BOOKTITLE = {Proceedings of the 2nd New Zealand Two-Stream Conference on Artificial Neural Nets and Expert Systems},
YEAR = 1995,
PAGES = {231-234},
ADDRESS = {Dunedin, New Zealand}
}
@INPROCEEDINGS{thomson02:_mobil_robot_path_track_using_visual_servoin,
AUTHOR = {Andrew Thomson and Jacky Baltes},
TITLE = {Mobile Robot Path Tracking Using Visual Servoing},
BOOKTITLE = {Proceedings of the International Conference on Vision Computing New Zealand},
YEAR = 2002,
ADDRESS = {Auckland, New Zealand},
MONTH = {November},
ABSTRACT = {This paper describes a path tracking controller for
mobile robots using visual servoing. A highly
efficient algorithm suitable for cheap and low power
micro-processor is described. The algorithm uses a
highly focused search in the image to approximate
the offset and gradient of the path. These features
are determined solely by a sweep through two rows of
the image. An empirical evaluation shows that the
algorithm is efficient and robustness. Furthermore,
the empirical evaluation investigates the
relationship between the average error and the look
ahead distance as well as the weighting between the
offset and gradient information.},
URL = {pdf/thomson02:_mobil_robot_path_track_using_visual_servoin.pdf},
SLIDES = {pdf/thomson02:_mobil_robot_path_track_using_visual_servoin_slides.pdf}
}
@INPROCEEDINGS{baltes03:_ident_robot_throug_behav_analy,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {Identifying Robots Through Behavioral Analysis},
BOOKTITLE = {Proceedings of the Second International Conference
on Computational Intelligence, Robotics, and
Autonomous Systems},
YEAR = 2003,
ADDRESS = {Singapore},
ANNOTE = {Identifying the location and orientation of robots is a
significant problem in vision for robotic soccer. Previous
approaches use some type of identifying marker system (coloured
spots, arrangements of bars) in order to facilitate fast visual
identification of individual robots. However, these methods do not
scale well to larger teams and require considerable calibration
effort. This paper describes an approach that does not require such
markers. Instead, the movement history as well and command history
are used to identity the robot by employing Bayesian techniques to
correlate the commands sent to the robot with the robot's actions in
the environment. This approach is implemented in the latest version
of our global video server, \Doraemon.}
}
@INPROCEEDINGS{baltes03:_stabil_walkin_gaits_using_feedb_from_gyros,
AUTHOR = {Jacky Baltes and Sara McGrath and John Anderson},
TITLE = {Stabilizing Walking Gaits Using Feedback From Gyroscopes},
BOOKTITLE = {Proceedings of the Second International Conference
on Computational Intelligence, Robotics, and
Autonomous Systems},
YEAR = 2003,
ANNOTE = {This paper describes methods used in stabilizing the
walking gait of Tao-Pie-Pie, a small humanoid robot given
rate feedback from two RC gyroscopes. Tao-Pie-Pie is a
fully autonomous small humanoid robot (30cm
tall). Although Tao-Pie-Pie uses a minimal set of
actuators and sensors, it has proven itself in
international competitions, winning honors at the
RoboCup and HuroSot competitions in 2002 and
2003. The feedback control law is based solely on
the rate information from two RC gyroscopes. This
alleviates drift problems introduced by integrating
the RC gyroscope feedback in the more common
position control approaches.}
}
@INPROCEEDINGS{baltes03:_learn_orien_infor_robot_soccer,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {Learning Orientation Information for Robotic Soccer
Using Neural Nets},
BOOKTITLE = {Proceedings of the FIRA World Congress},
YEAR = 2003,
ADDRESS = {Vienna, Austria},
MONTH = {October},
ANNOTE = {Robotic soccer teams using both local and global
vision traditionally rely on a set of pre-determined
markers (e.g., a group of small colored circles
mounted on the top surface of the robot) to provide
easy targets for visual analysis in order to
determine the team membership, identity, and
orientation of robots in the visual field. This
approach requires calibration before any
competition, as well as agreement in advance on
color codes different enough between teams to avoid
recognition errors at run-time. Even after extensive
calibration, small lighting variations can cause
extensive misidentification. In this paper, we
examine an alternative approach: training a neural
network to recognize the orientation of the robots
on a team so that visual tracking can occur in real
time without special markers of any kind. This paper
describes the design and implementation of such an
approach, and shows the results of an empirical
evaluation of this approach.}
}
@INPROCEEDINGS{baltes03:_feedb_contr_walkin_small_human_robot,
AUTHOR = {Jacky Baltes and Sara McGrath and John Anderson},
TITLE = {Feedback Control of Walking for a Small Humanoid Robot},
BOOKTITLE = {Proceedings of the FIRA World Congress},
YEAR = 2003,
ADDRESS = {Vienna, Austria},
MONTH = {October},
ANNOTE = {This paper describes methods used in stabilizing the
walking gait of Tao-Pie-Pie, a small humanoid robot given
rate feedback from two RC gyroscopes. Tao-Pie-Pie is a
fully autonomous small humanoid robot (30cm
tall). Although Tao-Pie-Pie uses a minimal set of
actuators and sensors, it has proven itself in
international competitions, winning honors at the
RoboCup\ and HuroSot\ competitions in 2002 and
2003. The feedback control law is based solely on
the rate information from two RC gyroscopes. This
alleviates drift problems introduced by integrating
the RC gyroscope feedback in the more common
position control approaches.}
}
@INPROCEEDINGS{wegner03:_blend_auton_teleop_intel_contr,
AUTHOR = {Ryan Wegner and John Anderson and Jacky Baltes},
TITLE = {Blending Autonomy and Teleoperation for Intelligent
Control of Multiple Mobile Robots in Urban Search
and Rescue Environments},
BOOKTITLE = {Proceedings of the FIRA World Congress},
YEAR = 2003,
ADDRESS = {Vienna, Austria},
MONTH = {October}
}
@INPROCEEDINGS{baltes03:_keyst_rescue,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {The Keystone Rescue Robotic Rescue Team},
BOOKTITLE = {Proceedings of the IJCAI Robotics Workshop},
YEAR = 2003
}
@INPROCEEDINGS{baltes03:_walkin_gaits_small_human_robot,
AUTHOR = {Jacky Baltes and Patrick Lam},
TITLE = {Walking Gaits for a Small Humanoid Robot},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003,
ADDRESS = {Padova, Italy}
}
@INPROCEEDINGS{anderson03:_towar_under_league_roboc,
AUTHOR = {John Anderson and Jacky Baltes and David Livingston and Elizabeth Sklar},
TITLE = {Toward an Undergraduate League for RoboCup},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003
}
@INPROCEEDINGS{baltes03:_flexib_binar_space_partit_robot_rescue,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {Flexible Binary Space Partitioning for Robotic Rescue},
BOOKTITLE = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
YEAR = 2003,
ADDRESS = {Las Vegas},
MONTH = {October},
ABSTRACT = {In domains such as robotic rescue, robots must plan
paths through environments that are complex and
dynamic, and in which robots have only incomplete
knowledge. This will normally require both
diversions from planned paths as well as significant
re-planning as events in the domain unfold and new
information is acquired. In terms of a
representation for path planning, these requirements
place significant demands on efficiency and
flexibility. This paper describes a method for
flexible binary space partitioning designed to serve
as a basis for path planning in uncertain dynamic
domains such as robotic rescue. This approach is
used in the 2003 version of the \kfb\, a robotic
rescue team. We describe the algorithm used, make
comparisons to related approaches to path planning,
and provide an empirical evaluation of an
implementation of this approach.},
URL = {pdf/baltes03:_flexib_binar_space_partit_robot_rescue.pdf},
SLIDES = {pdf/baltes03:_flexib_binar_space_partit_robot_rescue_slides.pdf}
}
@INPROCEEDINGS{anderson03:_littl_black_devil,
AUTHOR = {John Anderson and Jacky Baltes and Doug Cornelson
and Terry Liu and Clint Stuart and Adam Zilkie},
TITLE = {The Little Black Devils},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003,
ADDRESS = {Padova, Italy},
MONTH = {July}
}
@INPROCEEDINGS{anderson03:_univer_manit_uleag_team,
AUTHOR = {John Anderson and Jacky Baltes and Doug Cornelson
and Terry Liu and Clint Stuart and Adam Zilkie},
TITLE = {The University of Manitoba ULeague Team},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003,
ADDRESS = {Padova, Italy},
MONTH = {July}
}
@INPROCEEDINGS{anderson03:_keyst_rescue_team,
AUTHOR = {John Anderson and Jacky Baltes and Jay Kraut},
TITLE = {The Keystone Rescue Team},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003,
ADDRESS = {Padova, Italy},
MONTH = {July}
}
@INPROCEEDINGS{baltes03:_tao_pie_pie,
AUTHOR = {Jacky Baltes and Sara McGrath},
TITLE = {Tao-Pie-Pie},
BOOKTITLE = {Proceedings of the RoboCup Symposium},
YEAR = 2003,
ADDRESS = {Padova, Italy},
MONTH = {July}
}
@MANUAL{baltes04:_huros_laws_game,
TITLE = {HuroSot Laws of the Game},
AUTHOR = {Jacky Baltes and Thomas Br\"aunl},
ORGANIZATION = {University of Manitoba},
ADDRESS = {Winnipeg, Canada},
MONTH = {May},
YEAR = 2004,
NOTE = {http://www.fira.net/hurosot}
}
@INPROCEEDINGS{lee03:_applic_td_learn_openin_games_go,
AUTHOR = {Byung-Doo Lee and Hans Werner Guesgen and Jacky Baltes},
TITLE = {The Application of TD(l) Learning to the Opening Games of Go},
BOOKTITLE = {Proceedings of the Fifth International Conference on Advances in Pattern Recognition},
YEAR = 2003,
ADDRESS = {Kalkutta, India}
}
@ARTICLE{baltes04:_desig_walkin_gaits_tao_pie,
AUTHOR = {Jacky Baltes and Patrick Lam},
TITLE = {Design of Walking Gaits for Tao-Pie-Pie, a Small Humanoid Robot},
JOURNAL = {Advanced Robotics},
YEAR = 2004,
VOLUME = 18,
NUMBER = 7,
PAGES = {713-716},
MONTH = {August},
ABSTRACT = {This paper describes the methodology that we used to
design and implement balancing and walking gaits for
Tao-Pie-Pie, a small 30cm tall humanoid robot.
Tao-Pie-Pie is a fully autonomous robot with all
power, sensing, and processing done on-board. It is
also a minimalistic design with only six degrees of
freedom. Nevertheless, its performance is comparable
to that of other more complex designs. The paper
describes three patterns: (a) a straight walk, (b) a
turn on the spot, and (c) a kicking pattern. Sensor
feedback is provided by two gyroscopes that provide
angular velocity in the left-right and
forward-backward plane and a CMOS camera providing
vision information. The feedback from the gyroscopes
is not used to directly control the walking gait,
because the signal is noisy and it would be
computationally too expensive for the current
processor hardware. Instead, coarse feedback from
the gyroscopes is used to monitor the transition
from one phase of the pattern to the next. This
feedback is used to: (a) determine when a phase has
completed successfully, and (b) when to change the
endpoints of certain phases. Tao-Pie-Pie proved to be a
successful design winning a number of honors at
international competitions.},
URL = {pdf/baltes04:_desig_walkin_gaits_tao_pie.pdf}
}
@INPROCEEDINGS{baltes04:_teach_roboc,
AUTHOR = {Jacky Baltes and Elizabeth Sklar and John Anderson},
TITLE = {Teaching with RoboCup},
BOOKTITLE = {Accessible Hands-on Artificial Intelligence and
Robotics Education},
PAGES = {146 - 152},
YEAR = 2004,
NUMBER = {SS-04-01},
SERIES = {Spring Symposium},
MONTH = {February},
ORGANIZATION = {American Association for Artificial Intelligence},
PUBLISHER = {AAAI Press},
URL = {pdf/baltes04:_teach_roboc.pdf}
}
@INPROCEEDINGS{mckinnon04:_pract_region_based_match_stereo_vision,
AUTHOR = {Brian McKinnon and Jacky Baltes},
TITLE = {Practical Region-Based Matching for Stereo Vision.},
BOOKTITLE = {IWCIA},
PAGES = {726-738},
YEAR = 2004,
EDITOR = {Reinhard Klette and Jovisa D. Zunic},
VOLUME = 3322,
SERIES = {Lecture Notes in Computer Science},
PUBLISHER = {Springer},
ISBN = {3-540-23942-1},
URL = {pdf/mckinnon04:_pract_region_based_match_stereo_vision.pdf},
ABSTRACT = {Using stereo vision in the field of mapping and
localization is an intuitive idea, as demonstrated
by the number of animals that have developed the
ability. Though it seems logical to use vision, the
problem is a very difficult one to solve. It
requires the ability to identify objects in the
field of view, and classify their relationship to
the observer. A procedure for extracting and
matching object data using a stereo vision system is
introduced, and initial results are provided to
demonstrate the potential of this system.}
}
@INPROCEEDINGS{liu04:_intuit_flexib_archit_intel_mobil_robot,
AUTHOR = {Xiao-Wen Terry Liu and Jacky Baltes},
TITLE = {An Intuitive and Flexible Architecture for
Intelligent Mobile Robots},
BOOKTITLE = {Second International Conference on Autonomous Robots
and Agents (ICARA)},
PAGES = {52-57},
YEAR = 2004,
EDITOR = {S. C. Mukhopadhyay and G. Sen Gupta},
MONTH = {December},
ORGANIZATION = {Massey University},
ISBN = {0-476-00994-4},
ABSTRACT = {The goal of this research is to develop an
intuitive, adaptive, and flexible architecture for
intelligent mobile robots. We propose a hybrid
architecture that uses behaviour trees and finite
state machines. A task manager selects behaviours
based on approximations of their applicability and
the expected reward of a behaviour. One major
feature of this architecture is that important
information of the perception, reasoning, and
execution parts of the system are made
explicit. This information includes parameters
(e.g., colour definitions), structural information
(e.g., the behaviour tree), and the ability to
represent prototypical scenarios.},
URL = {pdf/liu04:_intuit_flexib_archit_intel_mobil_robot.pdf},
SLIDES = {pdf/liu04:_intuit_flexib_archit_intel_mobil_robot_slides.pdf}
}
@INPROCEEDINGS{mcgrath04:_activ_balan_using_gyros_small_human_robot,
AUTHOR = {Sara McGrath and Jacky Baltes and John Anderson},
TITLE = {Active Balancing Using Gyroscopes for a Small Humanoid Robot},
BOOKTITLE = {Second International Conference on Autonomous Robots
and Agents (ICARA)},
PAGES = {470-475},
YEAR = 2004,
EDITOR = {S. C. Mukhopadhyay and G. Sen Gupta},
MONTH = {December},
ORGANIZATION = {Massey University},
ISBN = {0-476-00994-4},
ABSTRACT = {This paper describes methods used in stabilizing the
walking gait of Tao-Pie-Pie, a small humanoid robot given
rate feedback from two RC gyroscopes. Tao-Pie-Pie is a
fully autonomous small humanoid robot (30cm
tall). Although Tao-Pie-Pie uses a minimal set of
actuators and sensors, it has proven itself in
international competitions, winning honors at the
RoboCup and HuroSot competitions in 2002 and
2003. The feedback control law is based solely on
the rate information from two RC gyroscopes. This
alleviates drift problems introduced by integrating
the RC gyroscope feedback in the more common
position control approaches.},
URL = {pdf/mcgrath04:_activ_balan_using_gyros_small_human_robot.pdf},
SLIDES = {pdf/mcgrath04:_activ_balan_using_gyros_small_human_robot_slides.pdf}
}
@INPROCEEDINGS{baltes04:_inter_method_global_vision_system,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {Interpolation Methods for Global Vision Systems},
BOOKTITLE = {The Seventh RoboCup Competitions and Conferences},
YEAR = 2005,
EDITOR = {Daniele Nardi and Martin Riedmiller and and Claude Sammut},
ADDRESS = {Berlin},
PUBLISHER = {Springer Verlag},
ABSTRACT = {In 2004, the playing field size of the small sized
league was significantly increased, which poses new
challenges for all teams. This paper describes
extensions to our current video server software
Doraemon to deal with these new challenges. It shows
that a camera with a side view is a workable
alternative to the more expensive approach of using
multiple cameras. To illustrate this point, the
paper discusses the camera calibration method used
in Doraemon as well as an investigation into some
common two dimensional interpolation methods (pulse,
linear, and cubic B-spline) as well a novel average
gradient method. It also proves that (ignoring
occluded parts of the playing field) it is possible
to construct a realistic top down view of the
playing field with a camera that only has a side
view of the field.},
URL = {pdf/baltes04:_inter_method_global_vision_system.pdf}
}
@INPROCEEDINGS{baltes05:_tao_pie_pie_human_robot,
AUTHOR = {Jacky Baltes and Sara McGrath and John Anderson},
TITLE = {The Use of Gyroscope Feedback in the Control of the
Walking Gaits for a Small Humanoid Robot},
BOOKTITLE = {The Seventh RoboCup Competitions and Conferences},
YEAR = 2005,
EDITOR = {Daniele Nardi and Martin Riedmiller and and Claude Sammut},
ADDRESS = {Berlin},
PUBLISHER = {Springer Verlag},
URL = {pdf/baltes04:_use_gyros_feedb_contr_walkin.pdf}
}
@INPROCEEDINGS{anderson05:_robob,
AUTHOR = {John Anderson and Jacky Baltes and Terry Liu},
TITLE = {RoboBisons 2004},
BOOKTITLE = {The Seventh RoboCup Competitions and Conferences},
YEAR = 2005,
EDITOR = {Daniele Nardi and Martin Riedmiller and and Claude Sammut},
ADDRESS = {Berlin},
PUBLISHER = {Springer Verlag}
}
@INPROCEEDINGS{baltes05:_keyst_fire_brigad,
AUTHOR = {Jacky Baltes and John Anderson and Shawn Schaerer and Ryan Wegner},
TITLE = {Keystone Fire Brigade 2004},
BOOKTITLE = {The Seventh RoboCup Competitions and Conferences},
YEAR = 2005,
EDITOR = {Daniele Nardi and Martin Riedmiller and and Claude Sammut},
ADDRESS = {Berlin},
PUBLISHER = {Springer Verlag}
}
@INPROCEEDINGS{baltes05:_tao_pie_pie_human_robot2,
AUTHOR = {Jacky Baltes and Sara McGrath and John Anderson},
TITLE = {Tao-Pie-Pie Humanoid Robot},
BOOKTITLE = {The Seventh RoboCup Competitions and Conferences},
YEAR = 2005,
EDITOR = {Daniele Nardi and Martin Riedmiller and and Claude Sammut},
ADDRESS = {Berlin},
PUBLISHER = {Springer Verlag}
}
@INPROCEEDINGS{baltes04:_introd_progr_works_child_using_robot,
AUTHOR = {Jacky Baltes and John Anderson},
TITLE = {Introductory Programming Workshop for Children Using Robotics},
BOOKTITLE = {Proceedings of the 2nd International Symposium on Robotics Education},
YEAR = 2004,
ADDRESS = {Daejon, Korea},
MONTH = {November},
ORGANIZATION = {KAIST}
}
@INPROCEEDINGS{anderson04:_reinf_learn_teamm_varyin_skill_robot_soccer,
AUTHOR = {John Anderson and Brian Tanner and Jacky Baltes},
TITLE = {Reinforcement Learning from Teammates of Varying Skill in Robotic Soccer},
BOOKTITLE = {Proceedings of the 2004 FIRA Robot World Congress},
YEAR = 2004,
ADDRESS = {Busan, Korea},
MONTH = {October},
ORGANIZATION = {FIRA}
}
@INPROCEEDINGS{mcgrath04:_activ_balan_small_human_robot,
AUTHOR = {Sara McGrath and Jacky Baltes and John Anderson},
TITLE = {Active Balancing in a Small Humanoid Robot},
BOOKTITLE = {Proceedings of the 2004 FIRA Robot World Congress},
YEAR = 2004,
ADDRESS = {Busan, Korea},
MONTH = {October},
ORGANIZATION = {FIRA}
}
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