Description
- Course Title: Nonlinear Control and Planning in Robotics
- Course Number: EN530.678
- Time: MW 3:00-4:15
- Location: Hodson 316
- Professor: Marin Kobilarov
- Contact: marin(at)jhu.edu, Hackerman 117
- Office Hours: Monday 12:00-1:00, Hackerman 117
- Teaching Assistants
- Gabe Baraban (gbaraba1(at)jhu.edu), Rajni Bansal (rbansal3(at)jhu.edu), Tianqi Zheng (tzheng8(at)jhu.edu)
- TA Office Hours: Monday 11:00-12:00 and Friday 11:00-12:00, Hackerman 111
- Course material (homeworks/projects) can be submitted using the file upload formĀ
The course starts with a brief introduction to nonlinear systems and covers selected topics related to model-based trajectory planning and feedback control. Focus is on applications to robotic systems modeled as underactuated mechanical systems subject to constraints such as obstacles in the environment. Topics include: nonlinear stability, controllability, stabilization, trajectory tracking, systems with symmetries, differential flatness, backstepping, probabilistic roadmaps, stochastic optimization. Recommended Course Background: multi-variable/differential calculus, differential equations, linear algebra, undergraduate linear control, basic probability theory, programming in MATLAB; an introductory robotics course is useful but not required.
Objectives
- Basic analysis and stability of nonlinear systems
- Controllability of nonholonomic systems
- Stabilization and tracking of underactuated/nonholonomic systems
- Trajectory generation using differential flatness/symmetries
- Optimal trajectory generation: gradient/gradient-free methods
- Motion planning with complex constraints
- Combining trajectory generation and feedback control: receding horizon control
Reading
There is no required textbook for the course. A list of relevant textbooks is provided below.
- Textbooks: General Nonlinear Control
- Sastry, “Nonlinear Systems: Analysis, Stability, and Control, 1999
- Khalil, “Nonlinear Systems, 1991
- Slotine, Li, “Applied Nonlinear Control, 1991
- Textbooks: Robot Control and Planning
- Murray, Li, Sastry, “Mathematical Introduction to Robotic Manipulation, 1994, Chapters 7,8 (available online)
- Choset, Lynch, Hutchinson, Kantor, Burgard, Kavraki and Thrun, “Principles of Robot Motion: Theory, Algorithms, and Implementations, 2006
- Lavalle, “Planning Algorithms, 2006, Chapters 14, 15 (available online)
- Spong, Hutchinson, Vidyasagar, “Robot Modeling and Control, 2005
- edited by Laumond, “Robot motion planning and control, 1998
- Canudas de Wit, Siciliano, Bastin, “Theory of Robot Control, 1996
- Textbooks for additional/advanced background:
- Manifolds/Basics:
- “Calculus on manifolds”, Spivak, 1965
- Differential Geometry:
- “A Comprehensive Introduction to Differential Geometry”, Spivak
- “An Introduction to Differentiable Manifolds and Riemannian Geometry”, Boothby
- Mechanics
- “Mathematical Methods of Classical Mechanics”, Arnold, 1987
- “Introduction to Mechanics and Symmetry”, Marsden and Ratiu, 1999
- “Nonholonomic Mechanics and Control”, Bloch, 2003
- “Geometric Control of Mechanical Systems”, Bullo, Lewis, 2004
- Manifolds/Basics:
Schedule (tentative — check often!)
Week | Topic | Lecture Notes | Code | Assignments |
---|---|---|---|---|
1/27/2020 | Introduction, preliminaries, system models | Intro Lecture #1 Lecture #2 | ||
2/3/2020 | Nonlinear Stability | Lecture #3 | lecture3_1.m lecture3_2.m hw1_lyapunov_example.m | Homework #1 due Feb 12 |
2/12/2020 | Nonlinear Stability (cont'd) | hw2_example.m | Homework #2 due Feb 19 | |
2/17/2020 | Manifolds and Vector Fields | Lecture #4 | lecture4_1.m | |
2/24/2020 | Controllability and Nonholonomy | Lecture #5 | Homework #3 due Mar 4 | |
2/26/2020 | Stabilizability and Nonholonomic Steering | Lecture #6 | ||
3/2/2020 | Differential Flatness | Lecture #7 | uni_flat_care.m arm_test.m | Homework #4 due Mar 11 |
3/4/2020 | Feedback Linearization | Lecture #8 | uni_flat_fl.m | Homework #5 due 3/25 |
3/30/2020 | Backstepping | Lecture #9 | unit_flat_bs.m | Homework #6 due 4/8 |
4/10/2020 | Lyapunov Redesign and Robustness | Lecture #10 | Homework #6 due 4/15 | |
4/12/2020 | Numerical Optimal Control | Lecture #11 | car_shooting.m ddp.zip cem.m cem_test.m | for further reading see these notes |
4/15/2020 | Sampling-based Motion Planning, Stochastic Trajectory Optimization | Lecture #12 | Stochastic Policy Optimization (SPO): spo.zip , Cross-entropy trajectory optimization: cem_planning_test.m D*-Lite Path Planning | |
4/27/2020 | Receding Horizon Control | Lecture #13 | ||
4/29/2020 | Control on Euclidean Groups | rb.zip |
Grading Policy
There will be homeworks given every week and due one week later (on Wednesday before class). There will be a midterm and a final covering the first half and second half of the semester, and a project involving both analys and implementation (e.g. in MATLAB). Grades will be determined according to:
Homeworks | 30% |
Midterm | 25% |
Final | 25% |
Project | 20% |
Ethics
You can work together with other students to study the material related to homeworks/tests but the submitted work must be entirely your own. For more information, see the guide on “Academic Ethics for Undergraduates” and the Ethics Board web site (http://ethics.jhu.edu).
Late homework will not be accepted without a prior approval from the instructor.