ECE 417/598: Introduction to Mobile Robotics
Spring 2022
Vikas Dhiman
Motivation
The definition of Robots has been a receding definition. Humanoids that can do everything autonomously have always been and still called Robots; but Roombas are just “smart” vacuum cleaners now and Teslas are just “Full Self Driving” vehicles—no longer Robots. This course focuses on Mobile Robots: the robots like Roombas and Teslas that move around. This is in contrast to Robotic arms installed in factories for automatic production. We will spend a lecture or two on Robotic arms, but there is an entire course dedicated to those: MEE 444. In this course, we will focus on getting a taste of and understanding the basics of a wide range of Robotics technology, using the open-source Robotic Operating Systems (ROS) framework as an entry point. ROS supports many programming languages, including Python and C++. We will cover basic algorithms for robotic Perception (understanding the world around the robot), Planning and control (taking action on the world to achieve a desired outcome).
Instructors and office hours
- Vikas Dhiman [email protected]; Barrows Hall Rm 105, Th 3-5 PM.
- Sarah Meyer-Waldo [email protected]; TBD ; Thu 10-11 AM;
Prerequisite:
- Programming knowledge to learn Python/C++.
- Math knowledge equivalent to MAT 128.
Textbook:
Robotics, Vision & Control, Peter Corke, Springer Verlag (2011). Search on libgen.rs for a pdf.
Additional references
- Programming Robots with ROS, O’Reilly Media, Inc (2015).
- Probabilistic Robotics. Sebastian Thrun, Wolfram Burgard, and Dieter Fox. (2005, MIT Press.)
Background references
- Introduction to Linear Algebra, Fifth Edition (2016) by Gilbert Strang.
- Programming – Principles and Practice Using C++ (2014) by Bjarne Stroustrup.
Topics (tentative)
- Introduction to Robotics
- Representing position and orientation (Chapter 2)
- Robot Operating Systems
- Mobile Robotics/Test system
- Sensing / GNSS
- Images (Chapter 11)
- Image Processing (Object detection, Chapter 12)
- Visual Tracking (Chapter 15)
- Visual Servoing (Chapter 16)
- Mapping (Chapter 6)
- Kalman
- Localization and Mapping (Chapter 6)
- Planning - Spaces and Search (Chapter 5)
- Planning - Sampling based methods (Chapter 5)
- Grasping & Hands
- Human Robot Interaction
- Architectures
- Ethics
Evaluation Components
Homework: 25%; Midterm Exam: 20%; Labs: 25%; and Final project: 30%
Similar courses
- CSE276A from UCSD by Prof Henrik Christensen
- https://www.youtube.com/c/JustinHuang101/
- ECE 276A from UCSD by Prof Nikolay Atanasov
- ECE 276b from UCSD by Prof Nikolay Atanasov
Student Learning Outcomes (SLOs)
Upon completion of the course, students will be able to:
- SLO 1: Use and extend open-source framework for Robotics: ROS
- SLO 2: Understand basic Robotics algorithms in: Exploration, Perception, Planning, Control
- SLO 3: Understand basic AI algorithms for object detection, segmentation, RL
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