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MRfall15

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Changed lines 94-95 from:
This course will deliver two Core Curriculum 2015 Essential Learning Outcomes (ELOs) in the Computer Science degree program: Applied and Integrative Learning (AIL) and Information Literacy (IL).
to:
This course will deliver two Core Curriculum 2015 Essential Learning Outcomes (ELOs) in the Computer Science undergraduate degree program: Applied and Integrative Learning (AIL) and Information Literacy (IL).
Changed line 112 from:
Specifically in the field of computer science, you will learn about how to conduct literature reviews, and you will learn how to interpret state-of-the-art research results for your own original work.
to:
Specifically in the field of computer science, you will learn to conduct literature reviews, and you will learn how to use state-of-the-art research results in interpreting your own original work.
Deleted lines 91-92:

(:html:)<p>&nbsp;</p>(:htmlend:)
Changed line 93 from:
!!
to:
(:html:)<p>&nbsp;</p>(:htmlend:)
Added lines 92-93:

!!
Changed lines 100-101 from:
The semester project will require you to set your own challenge based on the concepts learned in this class but also all of your knowledge from your prior courses. You will be expected to reach for something where you don't already know the answer, document your process of investigation, and your conclusions.
to:
The semester project will require you to set your own challenge based on the concepts learned in this class but also all of your knowledge from your prior courses. You will be expected to reach for something where you don't already know the answer, document your process of investigation, and your conclusions.

Thus, you will use your computer science knowledge in an integrative and applied way to accomplish the project
.
Changed line 112 from:
You will learn about how to conduct literature reviews, and you will learn how to interpret state-of-the-art research results for your own original work.
to:
Specifically in the field of computer science, you will learn about how to conduct literature reviews, and you will learn how to interpret state-of-the-art research results for your own original work.
Changed lines 94-99 from:
This course will deliver two Essential Learning Outcomes (ELOs) as part of an undergraduate degree in computer science:

*
Applied and Integrative Learning (AIL)
* Information Literacy (IL)

These will be accomplished as follows, both based on your work on the semester project.
to:
This course will deliver two Core Curriculum 2015 Essential Learning Outcomes (ELOs) in the Computer Science degree program: Applied and Integrative Learning (AIL) and Information Literacy (IL).
Changed line 119 from:
!! Graduate versus undergraduate section
to:
!! Graduate vs. Undergraduate section
Changed lines 117-121 from:
The project will be graded with a rubric to assess this learning outcome.
to:
The project will be graded with a rubric to assess this learning outcome.

!! Graduate versus undergraduate section

The graduate section of the course will have a longer paper as part of the semester project
.
Changed lines 91-117 from:
In short: the work you submit must be your own; do not help others cheat; cite prior work that you use.
to:
In short: the work you submit must be your own; do not help others cheat; cite prior work that you use.

!!Core Curriculum 2015 Essential Learning Outcomes
This course will deliver two Essential Learning Outcomes (ELOs) as part of an undergraduate degree in computer science:

* Applied and Integrative Learning (AIL)
* Information Literacy (IL)

These will be accomplished as follows, both based on your work on the semester project.

!!!Applied and Integrative Learning

->Definition: Applied and Integrative Learning is an understanding and disposition that a student builds across curriculum and co-curriculum, fostering learning between courses or by connecting courses to experiential learning opportunities.

The semester project will require you to set your own challenge based on the concepts learned in this class but also all of your knowledge from your prior courses. You will be expected to reach for something where you don't already know the answer, document your process of investigation, and your conclusions.

The project will be graded with a rubric to assess this learning outcome.

!!!Information Literacy (IL)

->Definition: The ability to use digital technologies, communication tools and/or networks to define a problem or an information need; devise an effective search strategy; identify, locate, and evaluate appropriate sources; and manage, synthesize, use and effectively communicate information ethically and legally.

As part of the semester project, you will do a literature review of related work. The class will provide you with guidance on how to do this. You will describe how this prior work has influenced your planning, and you will describe how your results are related to this prior research.

You will learn about how to conduct literature reviews, and you will learn how to interpret state-of-the-art research results for your own original work.

The project will be graded with a rubric to assess this learning outcome.
Changed line 3 from:
!91.451 Robotics II (ugrad) / 91.549 Mobile Robots (grad)
to:
!91.451 Mobile Robotics II (ugrad) / 91.549 Mobile Robots (grad)
Changed lines 12-17 from:

As of AY 2015–2016, for the [[undergrad version->https://www.uml.edu/Catalog/Courses/undergraduate/91-451.aspx]]:

->Advanced topics in robotics, including laboratory. Topics to be covered include probabilistic methods
, including sensor modeling, hidden Markov models, particle filters, localization, and map making. Research-level robots are used in the laboratories.

->
'''Pre/Co-Requisites:''' Pre-req: 91.450 Mobile Robotics I, and Co-req: 92.386 Probability and Statistics I.
to:
->Advanced topics in robotics, including laboratory. Topics to be covered include probabilistic methods, including sensor modeling, hidden Markov models, particle filters, localization, and map making. Research-level robots are used in the laboratories.  '''Pre/Co-Requisites:''' Pre-req: 91.450 Mobile Robotics I, and Co-req: 92.386 Probability and Statistics I.

->[-''academic year 2015–2016, for the [[undergrad version->https://www.uml.edu/Catalog/Courses/undergraduate/91-451.aspx]]''-]
Changed lines 35-36 from:
* per the listed requisites, prior or current enrollment is 92.386 Probability and Statistics I (or equivalent) is expected.
* you must have a solid programming background.
to:
* per the listed requisites, prior or current enrollment is 92.386 Probability and Statistics I (or equivalent).
* a solid programming background.
Changed lines 38-41 from:
* you must have Unix expertise (or the willingness to learn it).

To be clear on the latter point: For technical reasons, '''Windows may not be used at the host platform for course work—except as an environment for running Linux using VirtualBox or VMware.'''
to:
* Unix expertise (or the willingness to learn it).

To be clear on the latter point: For technical reasons, '''Windows may not be used at the host platform for course work—except as an environment for running Linux using VirtualBox or VMware.''' Computers will be available in Olsen 302 with the proper configuration.
Changed lines 55-58 from:
ROS will allow us to develop control programs for simulated robots, including the ability to process robot-centric camera views and laser ranger data.

You will develop a control program for a simulated robot in a simulated world, and then be able to seamlessly run that control program on our actual robot running in the real world. The use of the simulation tools are essential, given the amount of work involved in creating successful control programs and the relatively low availability of live robot time in the field.
to:
ROS will allow us to develop control programs for simulated robots, including the ability to process robot-centric laser ranger data.

You will develop a control program for a simulated robot in a simulated world, and then be able to seamlessly run that control program on real robots running in the real world. The use of the simulation tools are essential, given the amount of work involved in creating successful control programs and the relatively low availability of live robot time in the field.
Changed lines 63-64 from:
The course will have a final project, in which you will create a problem, study it, and solve.
to:
After this, the course will have a semester project, in which you will create a problem, study it, and solve it.
Changed line 92 from:
I expect you to follow the university's policies on academic integrity ([[undergrad->http://www.uml.edu/Catalog/Undergraduate/Policies/Academic-Policies/Academic-Integrity.aspx]]; [[grad->https://www.uml.edu/Catalog/Graduate/Policies/Academic-Integrity.aspx]]).
to:
I expect you to follow the university’s policies on academic integrity ([[undergrad->http://www.uml.edu/Catalog/Undergraduate/Policies/Academic-Policies/Academic-Integrity.aspx]]; [[grad->https://www.uml.edu/Catalog/Graduate/Policies/Academic-Integrity.aspx]]).
Changed line 67 from:
You can use prior work done in Robotics I last semester.
to:
You may build upon prior robot work done in Robotics I / Robot Design.
Changed lines 69-72 from:
Also, we have a number of Bilibot robots, which are an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department. The company is no longer operating, but the co-developer is available to help us get our robots running.)

!!Discussion group and email list
to:
Also, we have a number of Bilibot robots, which are an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department. The company that made it is no longer operating, but the co-developer is available to help us get our robots running.)

!! Discussion group and email list
Changed lines 87-89 from:
Each student is responsible for their own work for the weekly assignments. Teams of two will be encouraged for the final project. Teams of three will be allowed only with a clear plan for the work.
to:
Each student is responsible for their own work for the weekly assignments.

For the final project, teams of two persons will be encouraged.
Teams of three will be allowed only with a plan for the work that gives each team member a clear and distinct role.
Changed lines 90-92 from:
I expect you to follow the university's policies on academic integrity [undergrad; grad].

In short
: work you submit must be your own; do not help other students cheat; cite prior work that you use.
to:
I expect you to follow the university's policies on academic integrity ([[undergrad->http://www.uml.edu/Catalog/Undergraduate/Policies/Academic-Policies/Academic-Integrity.aspx]]; [[grad->https://www.uml.edu/Catalog/Graduate/Policies/Academic-Integrity.aspx]]).

In short: the work you submit must be your own; do not help others
cheat; cite prior work that you use.
Changed line 69 from:
Also, we have a number of Bilibot robots, which are an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department.)
to:
Also, we have a number of Bilibot robots, which are an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department. The company is no longer operating, but the co-developer is available to help us get our robots running.)
Added lines 42-43:
The course will also require you to be a self-directed learner, seeking out solutions to only partially-structured problems, and ultimately specifying and carrying out your own final project.
Changed lines 59-74 from:
We will develop code in simulation and then run it on the Bilibot, an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department.)

Robot control tasks will include:
* localization—determining the robot's location and position (pose) within a known map of the surroundings
* mapping—dynamically building a map of the robot's surroundings
* sensor filtering—e.g., combining data from
a rate-gyro and wheel encoders to determine robot position; interpreting data from a 3d point cloud
* coordinate transformations—e.g.,translating reference frames of sensors or effectors mounted on the robot's body to the center of the robot
* manipulation—using a robot arm or the robot's own body to cause changes in the world

Our work will also be driven by the Intelligent Ground Vehicles Competition challenge, which combines localization, mapping, and navigation tasks in an outdoor environment
. Robots must visit waypoints in a 1-acre field (using GPS data) and stay inside a pair of painted lines in a one-tenth mile outdoor course, all while dealing with the presence of barrels, sawhorses, and other physical obstacles. See www.igvc.org for more details.

This year's IGVC competition will be held June 8–11, 2012. Students who participate in the course will be invited to make the road trip to Oakland, Michigan (just north of Detroit) to enter the contest. Partial funding to support the trip will be available.



to:
!! Projects

All of the weekly problem sets will be conducted in simulation
, using ROS.

The course will have a final project, in which you will create a problem, study it
, and solve.

You may continue work in simulation, or you may implement work on a physical robot.

You can use prior work done in Robotics I last semester.

Also, we have a number of Bilibot robots, which are an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard,
a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department.)
Changed lines 87-92 from:
Each student is responsible for their own work for the weekly assignments. Teams of two will be encouraged for the final project. Teams of three will be allowed only with a clear plan for the work.
to:
Each student is responsible for their own work for the weekly assignments. Teams of two will be encouraged for the final project. Teams of three will be allowed only with a clear plan for the work.

!!Academic Integrity
I expect you to follow the university's policies on academic integrity [undergrad; grad].

In short: work you submit must be your own; do not help other students cheat; cite prior work that you use
.
Deleted lines 41-42:
Programming work will be conducted in the Ubuntu 14.04 “Trusty” platform. Python will be the preferred
Changed lines 49-51 from:

For practical work, we will use ROS, the robot operating system, an open-source robot simulation package and driver system. This will allow us to develop control programs for simulated robots, including the ability to process robot-centric camera views and laser ranger data.
to:
!! Practical work

Programming work
will be conducted in the Ubuntu 14.04 “Trusty” operating system. We will use the [[Robot Operating System->http://www.ros.org/]] (ROS) libraries and tools.

ROS
will allow us to develop control programs for simulated robots, including the ability to process robot-centric camera views and laser ranger data.
Changed lines 70-84 from:
!!Prerequisites and Expectations

The course
will exercise your mathematical background, specifically drawing on skills in calculus, discrete mathematics, linear algebra, and probability.

The course will require significant software implementation skills. Implementation work will be done using the ROS framework and writing code in (your choice of) Python or C++.

The course will also require you to be a self-directed learner, seeking out solutions to only partially-structured problems, and ultimately specifying and carrying out your own final project.

!!Discussion Group / E-Mail List

We will use Google Groups for class conversation and announcements. Please join this group.
Subscribe to 91451-548-s12
Email:

Browse Archives
to:



!!Discussion group and email list

We
will use Google Groups for class conversation and announcements. The group is @@mrfall15@googlegroups.com@@—Mobile Robots Fall ’15.

Click on the link [[Discussion Group]] here or at the top of the site to join.
Deleted line 78:
 
Added lines 87-89:

!!Teamwork
Each student is responsible for their own work for the weekly assignments. Teams of two will be encouraged for the final project. Teams of three will be allowed only with a clear plan for the work.
Changed lines 21-22 from:
This course will focus on the emerging field of probabilistic robotics.  We will study the probabilistic theory that allows a robot to build a robust model of the external world, even though it resides in a body that has noisy sensors and sloppy actuators. We'll begin by studying localization (the problem of figuring out a robot's position or “pose”) when given a world map. Topics include sensor modeling, hidden Markov models, particle filters, localization, and map making. We'll conclude with understanding the famous “simultaneous localization and mapping” (SLAM) algorithm, which is the basis of autonomous automobiles and other robotic systems.
to:
This course will focus on the emerging field of probabilistic robotics.  We will study the probabilistic theory that allows a robot to build a robust model of the external world, even though it resides in a body that has noisy sensors and sloppy actuators.

We'll begin by studying localization (the problem of figuring out a robot's position or “pose”) when given a world map.

As mentioned, topics include sensor
modeling, hidden Markov models, particle filters, localization, and map making.

We'll conclude with understanding the famous “simultaneous localization and mapping” (SLAM) algorithm, which is the basis of autonomous automobiles and other robotic systems.
Added lines 35-40:
* per the listed requisites, prior or current enrollment is 92.386 Probability and Statistics I (or equivalent) is expected.
* you must have a solid programming background.
* the preferred course language is Python; you must either have prior experience or be willing to learn it.
* you must have Unix expertise (or the willingness to learn it).

To be clear on the latter point: For technical reasons, '''Windows may not be used at the host platform for course work—except as an environment for running Linux using VirtualBox or VMware.'''
Changed lines 13-14 from:
As of AY 2015–2016:
to:
As of AY 2015–2016, for the [[undergrad version->https://www.uml.edu/Catalog/Courses/undergraduate/91-451.aspx]]:
Added lines 16-17:

->'''Pre/Co-Requisites:''' Pre-req: 91.450 Mobile Robotics I, and Co-req: 92.386 Probability and Statistics I.
Changed lines 11-14 from:
'''''WARNING SOME INFORMATION HAS NOT BEEN UPDATED FROM 2012'''''

This course will focus on the emerging field of probabilistic robotics.  We will study the probabilistic theory that allows a robot to build a robust model of the external world, even though it resides in a body that has noisy sensors and sloppy actuators. We'll begin by studying localization (the problem of figuring out a robot's position or “pose”) when given a world map.
We'll conclude with understanding the famous “simultaneous localization and mapping” (SLAM) algorithm, which is the basis of autonomous automobiles and other robotic systems.
to:
!!Catalog description

As of AY 2015–2016:

->Advanced topics in robotics, including laboratory. Topics to be covered include probabilistic methods, including sensor modeling, hidden Markov models, particle filters, localization, and map making. Research-level robots are used in the laboratories.

!!More course description

This course will focus on the emerging field of probabilistic robotics.  We will study the probabilistic theory that allows a robot to build a robust model of the external world, even though it resides in a body that has noisy sensors and sloppy actuators. We'll begin by studying localization (the problem of figuring out a robot's position or “pose”) when given a world map. Topics include sensor modeling, hidden Markov models, particle filters, localization, and map making
. We'll conclude with understanding the famous “simultaneous localization and mapping” (SLAM) algorithm, which is the basis of autonomous automobiles and other robotic systems.
Changed lines 23-25 from:
The course will have a strong implementation component.

!!Course text
to:
The course will have a strong implementation component. 

!! Expectations


Programming work will be conducted in the Ubuntu 14.04 “Trusty” platform. Python will be the preferred

!!
Course text
Deleted lines 36-38:

By the inventors of probabilistic robotics. 1990s mobile robotics work that's still relevant.
Both books are published by MIT Press and have been ordered at the UML Bookstore. A used copy is suggested for the Kortenkamp et al. book to save costs.
Deleted line 18:
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Attach:pr-text.jpg \\
to:
%height=180px% Attach:pr-text.jpg \\
Changed line 24 from:
Attach:pr-text.jpg
to:
Attach:pr-text.jpg \\
Changed lines 15-19 from:




We
will use two books—a text with strong theoretical basis, and a volume that's a paper collection of implementation stories of successful mobile robot designs:
to:
The course will focus on discrete methods. Continuous methods will be briefly mentioned as relevant.

The course will have a strong
implementation component.


!!Course text
Changed lines 22-27 from:
Probabilistic Robotics (2005)
Sebastian Thrun, Wolfram Burgard, & Dieter Fox
 
Artificial Intelligence and Mobile Robots
: 
Case Studies of Successful Robot Systems (1998)
D
. Kortenkamp, R. Peter Bonasso, R. Murphy (eds).
to:
Probabilistic Robotics (2005) \\
Sebastian Thrun, Wolfram Burgard, & Dieter Fox \\
Attach
:pr-text.jpg
[[http://www
.probabilistic-robotics.org/]]
Changed line 7 from:
(:html:)<a href="http://mailhide.recaptcha.net/d?k=01COSqrfJ-58cc94fQb2pI1A==&c=iZBP8kCznrjdnfw8QFFKADFtsIimnLdVHk581djoISQ=" onclick="window.open('http://mailhide.recaptcha.net/d?k=01COSqrfJ-58cc94fQb2pI1A==&c=iZBP8kCznrjdnfw8QFFKADFtsIimnLdVHk581djoISQ=', '', 'toolbar=0,scrollbars=0,location=0,statusbar=0, menubar=0,resizable=0,width=500,height=300'); return false;" title="Reveal this e-mail address">click for fred's email</a>,(:htmlend:) \\
to:
@@fredm@cs.uml.edu@@ \\
Changed lines 13-17 from:
This course will focus understanding and implementing control architectures for mobile robots that operate autonomously to accomplish specific tasks. There will be a specific focus on the emerging field of probabilistic robotics. The class will combine theory and practice, including the study of successful robot architectures and our own implementations.
to:
This course will focus on the emerging field of probabilistic robotics.  We will study the probabilistic theory that allows a robot to build a robust model of the external world, even though it resides in a body that has noisy sensors and sloppy actuators. We'll begin by studying localization (the problem of figuring out a robot's position or “pose”) when given a world map. We'll conclude with understanding the famous “simultaneous localization and mapping” (SLAM) algorithm, which is the basis of autonomous automobiles and other robotic systems.



Changed line 7 from:
fr...@...uml.edu \\
to:
(:html:)<a href="http://mailhide.recaptcha.net/d?k=01COSqrfJ-58cc94fQb2pI1A==&c=iZBP8kCznrjdnfw8QFFKADFtsIimnLdVHk581djoISQ=" onclick="window.open('http://mailhide.recaptcha.net/d?k=01COSqrfJ-58cc94fQb2pI1A==&c=iZBP8kCznrjdnfw8QFFKADFtsIimnLdVHk581djoISQ=', '', 'toolbar=0,scrollbars=0,location=0,statusbar=0, menubar=0,resizable=0,width=500,height=300'); return false;" title="Reveal this e-mail address">click for fred's email</a>,(:htmlend:) \\
Changed line 1 from:
[[MRspr15|Home]] [[Lecture Blog]] [[Resources]] [[Project]] [[Discussion Group]] [[Assignments]]
to:
[[MRfall15|Home]] [[Assignments]] [[Lecture Blog]] [[Resources]] [[Discussion Group]]
August 30, 2015, at 01:27 PM by 192.168.0.12 -
Changed line 1 from:
[[MRspr12|Home]] [[Lecture Blog]] [[Resources]] [[Project]] [[http://groups.google.com/group/91451-548-s12 | Discussion Group]] [[Assignments]]
to:
[[MRspr15|Home]] [[Lecture Blog]] [[Resources]] [[Project]] [[Discussion Group]] [[Assignments]]
August 30, 2015, at 01:08 PM by 192.168.0.12 -
Changed lines 3-7 from:
!Robotics II / Robot Design

!!91.451.201
(undergrad) and 91.548.201 (grad)
!!!Spring 2012

to:
!91.451 Robotics II (ugrad) / 91.549 Mobile Robots (grad)
!!!Fall 2015
Changed lines 8-9 from:
Tue/Thu, 12:30p – 1:45p  \\
OS403
to:
Tue/Thu, 3:30p – 4:45p  \\
OS402

'''''WARNING SOME INFORMATION HAS NOT BEEN UPDATED FROM 2012'''''
January 29, 2012, at 03:32 PM by Fred G Martin -
Changed lines 3-11 from:
Robotics II / Robot Design

91.451.201 (undergrad) and 91.548.201 (grad)
Spring 2012

Prof. Fred Martin
fr...@...uml.edu
Tue/Thu, 12:30p – 1:45p
OS403
to:
!Robotics II / Robot Design

!!91.451.201 (undergrad) and 91.548.201 (grad)
!!!Spring 2012

'''Prof. Fred Martin''' \\
fr...@...uml.edu \\
Tue/Thu,
12:30p – 1:45p  \\
OS403

Added line 14:
January 29, 2012, at 03:31 PM by Fred G Martin -
Added line 25:
Added line 27:
Added line 29:
Added line 31:
Changed lines 33-37 from:
localization—determining the robot's location and position (pose) within a known map of the surroundings
mapping—dynamically building a map of the robot's surroundings
sensor filtering—e.g., combining data from a rate-gyro and wheel encoders to determine robot position; interpreting data from a 3d point cloud
coordinate transformations—e.g.,translating reference frames of sensors or effectors mounted on the robot's body to the center of the robot
manipulation—using a robot arm or the robot's own body to cause changes in the world
to:
* localization—determining the robot's location and position (pose) within a known map of the surroundings
* mapping—dynamically building a map of the robot's surroundings
* sensor filtering—e.g., combining data from a rate-gyro and wheel encoders to determine robot position; interpreting data from a 3d point cloud
* coordinate transformations—e.g.,translating reference frames of sensors or effectors mounted on the robot's body to the center of the robot
* manipulation—using a robot arm or the robot's own body to cause changes in the world
Added line 40:
Changed lines 43-44 from:
Prerequisites and Expectations
to:
!!Prerequisites and Expectations
Added line 46:
Added line 48:
Changed lines 51-52 from:
Discussion Group / E-Mail List
to:
!!Discussion Group / E-Mail List
Changed lines 60-61 from:
Grading
to:
!!Grading
Changed lines 63-66 from:
30% Weekly assignments (problem sets and reading summaries)
20% Midterm (theory and programming)
35% Project (implementation and final paper)
15% Participation (classroom, lab, and online)
to:

30% Weekly assignments (problem sets and reading summaries)  \\
20%
Midterm (theory and programming) \\
35%
Project (implementation and final paper)  \\
15%
Participation (classroom, lab, and online) \\
January 28, 2012, at 08:54 PM by Fred G Martin -
Changed lines 3-58 from:
Mobile Robots spring 2012
to:
Robotics II / Robot Design

91.451.201 (undergrad) and 91.548.201 (grad)
Spring 2012

Prof. Fred Martin
fr...@...uml.edu
Tue/Thu, 12:30p – 1:45p
OS403
This course will focus understanding and implementing control architectures for mobile robots that operate autonomously to accomplish specific tasks. There will be a specific focus on the emerging field of probabilistic robotics. The class will combine theory and practice, including the study of successful robot architectures and our own implementations.
We will use two books—a text with strong theoretical basis, and a volume that's a paper collection of implementation stories of successful mobile robot designs:
 
Probabilistic Robotics (2005)
Sebastian Thrun, Wolfram Burgard, & Dieter Fox
 
Artificial Intelligence and Mobile Robots:
Case Studies of Successful Robot Systems (1998)
D. Kortenkamp, R. Peter Bonasso, R. Murphy (eds).
 

By the inventors of probabilistic robotics. 1990s mobile robotics work that's still relevant.
Both books are published by MIT Press and have been ordered at the UML Bookstore. A used copy is suggested for the Kortenkamp et al. book to save costs.
For practical work, we will use ROS, the robot operating system, an open-source robot simulation package and driver system. This will allow us to develop control programs for simulated robots, including the ability to process robot-centric camera views and laser ranger data.
You will develop a control program for a simulated robot in a simulated world, and then be able to seamlessly run that control program on our actual robot running in the real world. The use of the simulation tools are essential, given the amount of work involved in creating successful control programs and the relatively low availability of live robot time in the field.
We will develop code in simulation and then run it on the Bilibot, an open-source robotics platform that is based on an iRobot Create with an integrated Core i3 motherboard, a Microsoft Kinect point-cloud 3d sensor, and a custom arm. (The Bilibot was co-developed by an alum of the UML Computer Science Department.)
Robot control tasks will include:
localization—determining the robot's location and position (pose) within a known map of the surroundings
mapping—dynamically building a map of the robot's surroundings
sensor filtering—e.g., combining data from a rate-gyro and wheel encoders to determine robot position; interpreting data from a 3d point cloud
coordinate transformations—e.g.,translating reference frames of sensors or effectors mounted on the robot's body to the center of the robot
manipulation—using a robot arm or the robot's own body to cause changes in the world
Our work will also be driven by the Intelligent Ground Vehicles Competition challenge, which combines localization, mapping, and navigation tasks in an outdoor environment. Robots must visit waypoints in a 1-acre field (using GPS data) and stay inside a pair of painted lines in a one-tenth mile outdoor course, all while dealing with the presence of barrels, sawhorses, and other physical obstacles. See www.igvc.org for more details.
This year's IGVC competition will be held June 8–11, 2012. Students who participate in the course will be invited to make the road trip to Oakland, Michigan (just north of Detroit) to enter the contest. Partial funding to support the trip will be available.

Prerequisites and Expectations

The course will exercise your mathematical background, specifically drawing on skills in calculus, discrete mathematics, linear algebra, and probability.
The course will require significant software implementation skills. Implementation work will be done using the ROS framework and writing code in (your choice of) Python or C++.
The course will also require you to be a self-directed learner, seeking out solutions to only partially-structured problems, and ultimately specifying and carrying out your own final project.

Discussion Group / E-Mail List

We will use Google Groups for class conversation and announcements. Please join this group.
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Grading

The following plan will be used in determining course grades:
30% Weekly assignments (problem sets and reading summaries)
20% Midterm (theory and programming)
35% Project (implementation and final paper)
15% Participation (classroom, lab, and online)
January 28, 2012, at 08:43 PM by Fred G Martin -
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Mobile Robots spring 2012
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