Department of Computer Science
CSU Stanislaus
California State University
CS4710-001: Mobile
Robotics
Spring 2024
Instructor: Dr. Xuejun Liang
My Office: DBH 282
Office Hours: M 2:00PM-3:00PM &
WF 10:00AM-11:00AM (ZOOM Meeting ID 4438930033)
Phone: (209) 667-3169, Email: xliang@csustan.edu
Class Information:
Classroom: DBH 101 / Online
Class Date & Time: TR 12:30PM-1:45PM
Class Website: https://www.cs.csustan.edu/~xliang/Courses2/CS4710-24S
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Hybrid Online - Synchronous.
In-person class meetings will be on campus at the room, day, and time listed.
Online class meetings will be at the day and time listed. Students must be
available at the class times listed in the Class Schedule and must attend in
person on days indicated as such by the instructor. Students do not have the
option to choose in-person or virtual, nor opt for asynchronous participation |
Course Materials
Required
Textbook:
1.
Introduction
to AI Robotics, Second Edition, by Robin R. Murphy, The MIT Press, 2019
Reference Books:
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1. |
Introduction to Autonomous Mobile
Robots, Second Edition, by Roland Siegwart, IIIah Reza Nourbakhsh, and Davide Scaramuzza,
The MIT Press, 2011 |
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2. |
Probabilistic Robotics, by Sebastian Thrun, Wolfram Burgard, and Dieter Fox, The MIT Press, August 2005, ISBN: 9780262201629. |
Lecture Slides: Introduction to AI Robotics (Chapters 1-5 and 9-15)
· Ch01: What Are Intelligent Robots (Overview)
· Ch02: Brief History of AI Robotics (Overview)
· Ch03: Automation and Autonomy (Overview)
· Ch04: Software Organization: A (Operational Architectures) and B (System Architectures: 4b-1 and 4b2)
· Ch05: Teleoperation (Overview)
· Ch09: Locomotion (Overview)
· Ch10: Sensing (Overview)
· Ch11: Range Sensing (Overview)
· Ch12: Deliberation 12 (Overview)
· Ch13: Navigation 13 (Overview)
· Ch14: Metric Path Planning: A (Overview) and B (Motion planning)
· Ch15: Localization, Mapping, and Exploration: A (Overview) and B (Terrain)
Lecture Slides: Robotics Programing Assignments and Projects
· P1: Markov Location (P1A and P1B)
· P2: Kalman Localization (P2A and P2B)
· P3: Particle Filter (P3A, P3B and P3C)
· P4: Path Planning (P4)
· P5: Path Smoothing and PID Control (P5)
Course Syllabus and Major Topics
Course
Description
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CS4950 Robotics. (3 Hours) Pre-requisites: CS 3100 and MATH 2300. This course will introduce robotics and the key artificial intelligence issues involved in the development of intelligent robots. The course will examine algorithms for the control of autonomous mobile robots and explore issues that include software control architectures, localization, navigation, sensing, planning, and uncertainty. Provides a variety of hands-on robot programming and simulation projects. |
Course
Outcomes:
Students who successfully complete the course must
be able to
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1.
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Understand issues and concepts in autonomous mobile
robotics, problem statements, and typical applications. |
2.
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Understand
and apply mobile robot locomotion with legs and wheels and motion control,
and compute with and apply mobile robot kinematic models and constrains,
maneuverability, and workspace.
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3.
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Understand
and apply robotic sensing and perception, and master sensor performance,
sensor classification, uncertainty representation, and feature extraction.
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4.
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Understand
and apply algorithms and methodologies in the robot path planning,
localization, and map making.
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5.
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Write
software programs to control or simulate mobile robots on selected platforms
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