EN530.678.S2018 Nonlinear Control and Planning in Robotics


  • Course Title: Nonlinear Control and Planning in Robotics
  • Course Number: EN530.678
  • Time: MW 4:30-4:45
  • Location: Latrobe 107
  • Professor: Marin Kobilarov
    • Contact: marin(at)jhu.edu, Hackerman 117
    • Office Hours: M 3:00-4:00, Hackerman 117
  • Teaching Assistants
    • Matthew Sheckells (mshecke1(at)jhu.edu) , Gowtham Garimella (ggarime1(at)jhu.edu)
    • TA Office Hours: M 2:00-3:00, 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.


  • 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


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

Schedule (tentative — check often!)

WeekTopicLecture NotesCodeAssignments
1/29/2018Introduction, preliminaries, system modelsIntro
Lecture #1 Lecture #2
2/5/2018Nonlinear StabilityLecture #3lecture3_1.m lecture3_2.m Homework #1 due Feb 14
2/12/2018Nonlinear Stability (cont'd)hw2_example.m Homework #2 due Feb 21
2/19/2018Manifolds and Vector FieldsLecture #4lecture4_1.mHomework #3 due Feb 28
2/26/2018Controllability and NonholonomyLecture #5
2/28/2018Stabilizability and Nonholonomic SteeringLecture #6Homework #4 due Mar 7
3/5/2018Differential FlatnessLecture #7 uni_flat_care.m arm_test.mHomework #5 due Mar 14
Homework #6 due Mar 28
3/12/2018Feedback LinearizationLecture #8uni_flat_fl.mHomework #7 due Apr 4
3/19/2018Spring Break
3/26/2018Review and MidtermMidterm on 3/28
4/2/2018BacksteppingLecture #9 unit_flat_bs.mHomework #8 due 4/11
4/9/2018Lyapunov Redesign and RobustnessLecture #10
4/13/2018Numerical Optimal ControlLecture #11car_shooting.m ddp.zip cem.m cem_test.m for further reading see these notes
4/20/2018Sampling-based Motion Planning, Stochastic Trajectory OptimizationLecture #12Stochastic Policy Optimization (SPO): spo.zip ,
Cross-entropy trajectory optimization: cem_planning_test.m
D*-Lite Path Planning

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%


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.