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Course Information: ELLIIT Ph.D. Course on Motion Planning and Control, 6+3 hp


A course in advanced motion planning and control is to be held at the Division of Vehicular Systems, Linköping University during the spring semester 2021. The course is open for all Ph.D. students as well as senior undergraduate students. The course will cover both fundamental algorithms and state-of-the-art methods for motion planning and control. A significant part of the course will be dedicated to implementation of a number of selected algorithms and subsequent applications on small examples, to the purpose of gaining an understanding of the considered methods. The course relates to ongoing research within several programs, such as ELLIIT and WASP.


In the course, there will be approximately one meeting per week, see detailed course plan below. For each meeting in the course, one participant will be assigned in advance to prepare a short lecture (approximately 45 minutes) based on the reading material that has been studied by all course participants during that week. The assigned participant is also expected to, together with the course responsible teachers, lead a joint discussion in the group on the material after the lecture. During this discussion, both the algorithms themselves and other related aspects that have appeared when implementing them are covered.


In connection with selected course meetings, a hand-in assignment will be requested. The assignment should be submitted to the course responsible prior to each course occasion, since the exercises will be discussed during the meeting. No written reports are required for the hand-in assignments, but the implementation code and scripts with comments should be submitted. The participant should also be prepared to present and discuss the solutions in class.


The course will be divided into two parts. The first part will focus on motion planning and an introduction to motion control; this part will give 6 hp. The second part will focus on more advanced aspects of combined motion planning and control, and will also comprise a specialization part where the participant performs a slightly larger theoretical or experimental evaluation of a selected method, preferably related to the research field of the participant. The assignment could, e.g., be based on the Open Motion Planning Library (OMPL, http://ompl.kavrakilab.org/), the PythonRobotics Toolbox (https://pythonrobotics.readthedocs.io/en/latest/index.html), or the Robot Operating System (ROS, http://www.ros.org/). The second part of the course will give 3 hp.

Guest Lectures

Guest lectures will be given by invited speakers later in the course. They will give focused lectures on specific topics related to their own research. The speakers and exact times will be announced in the course plan below.


The planning part is based on the book:
  • LaValle, S. M., Planning Algorithms, Cambridge University Press, Cambridge, UK, 2006, which is available for free download at the homepage of the author:
  • Selected chapters from B. Siciliano & O. Khatib (Eds.) Springer Handbook of Robotics, 2nd Edition, 2016, will also be used as literature, which is available here:
  • The control part will be based on selected book chapters.
  • The books will be complemented by several articles and papers (announced during each meeting for the following week).


In order to receive course credits, the participant is required to:
  • Attend the weekly meetings and actively take part in the discussions.
  • Submit the hand-in assignments prior to each meeting where it is requested (primarily implementation code or scripts with comments and conclusions from the results, no extensive written reports required).
  • Prepare one lecture during the course.
  • Complete a final project, give an oral presentation at the project seminar, and submit a written report.
  • The course is nominally 6+3 hp (where the first part primarily comprises the planning part).
Examiner for the course is Björn Olofsson.

Course Plan

The course meetings and associated reading and implementation assignments are specified in the list below.

Introduction Meeting

Date: Tuesday January 12, 2021, at 15:15-16:15 in Zoom (link distributed to registered participants via e-mail).
Topics: About the course, introduction of participants, course administration, and planning of next meeting.
Responsible: Björn Olofsson
Slides: [Link]

Introduction to Motion Planning and Control & Discrete Graph Search

Date: Tuesday January 19, 2021, at 15:15-17:00 in Zoom.
Topics: Introduction to motion planning and control, overview of methods and their applicability, and graph-search algorithms (such as Dijkstra, A*, ARA*).
Responsible: Björn Olofsson
Assignments: [Link]
Links to material:

Motion-Planning Fundamentals

Date: Tuesday January 26, 2021, at 15:15-17:00 in Zoom.
Topics: Geometric representations, configuration and state spaces, and optimal paths for some wheeled vehicles.
Responsible: Faseeh Ahmad
Assignments: [Link]
Links to material:

Rapidly-Exploring Random Trees (RRTs) and Variants

Date: Tuesday February 2, 2021, at 15:15-17:00 in Zoom.
Topics: RRT, RRT*, CL-RRT, sampling-based planning with differential motion constraints.
Responsible: Anja Hellander
Assignments: [Link]
Links to material:

Motion Primitives and Lattice Planning

Date: Tuesday February 9, 2021, at 15:15-17:00 in Zoom.
Topics: Motion primitives, discretization of state space, state lattices, and lattice planning using graph search.
Responsible: Jian Zhou
Assignments: [Link]
Links to material:

Feedback-Based Planning and Artificial Potential Fields

Date: Tuesday February 16, 2021, at 15:15-17:00 in Zoom.
Topics: Planning using feedback methods, navigation functions, and artificial potential fields.
Responsible: Theodor Westny
Assignments: [Link]
Links to material:

Trajectory Optimization for Planning and Control

Date: Tuesday March 9, 2021, at 15:15-17:00 in Zoom.
Topics: Trajectory optimization, numerical optimal control, and optimization-based planning methods.
Responsible: Julian Salt
Assignments: [Link]
Links to material:

Motion Prediction for Planning and Control

Date: Tuesday March 16, 2021, at 15:15-17:00 in Zoom.
Topics: Vehicle-motion prediction and vehicle-intent prediction.
Responsible: Carl Hynén
Assignments: [Link]
Links to material:

Path and Trajectory-Following Control

Date: Tuesday March 23, 2021, at 15:15-17:00 in Zoom.
Topics: Path and trajectory following for wheeled vehicles.
Responsible: Birgitta Wingqvist
Assignments: [Link]
Links to material:

Motion Planning and Control Using Invariant Sets

Date: Tuesday April 6, 2021, at 15:15-17:00 in Zoom.
Topics: Invariant sets for motion planning and control, and design for robustness to disturbances.
Guest lecturer: Karl Berntorp, Mitsubishi Electric Research Labs, Boston, MA
Assignments: [Link]
Links to material:

Model Predictive Control for Planning and Control

Date: Tuesday April 13, 2021, at 15:15-17:00 in Zoom.
Topics:Receding-horizon control and model predictive control for path following, trajectory following, and integrated planning and control for autonomous vehicles.
Responsible: Jonas Nordlöf
Assignments: [Link]
Links to material:

Motion Planning Using Numerical Optimal Control

Date: Tuesday April 20, 2021, at 15:15-17:00 in Zoom.
Topics: Planning using numerical optimal control, receding-horizon planning, and planning for surface vehicles.
Guest lecturer: Kristoffer Bergman, Division of Automatic Control, Linköping University
Assignments: [Link]
Links to material:

Project Seminar

Date: Friday May 28, 2021, at 13:15-15:45 in Zoom.
Topics: Presentations of projects by participants.
Responsible: Björn Olofsson
Project organization: [Link]
Agenda: [Link]

Course Responsible

Responsible for the course is Björn Olofsson (bjorn.olofsson@liu.se) and Erik Frisk (erik.frisk@liu.se) at the Division of Vehicular Systems, Department of Electrical Engineering, Linköping University.

Informationsansvarig: Björn Olofsson
Senast uppdaterad: 2021-05-24