course-details-portlet

TTK4192 - Mission Planning for Autonomous Systems

About

Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Assignment 2/10
School exam 8/10 4 hours B

Course content

Path Planning: Recap from differential geometry and numerical analysis, including properties of parametric 2D/3D curves, curvature and torsion, interpolation/approximation. Overview of vehicle kinematic and dynamic constraints and their connection to path planning. Basic path generation for connecting waypoints: Dubins paths, Reeds-Shepp car, splines, Pythagorean Hodographs, spirals. Obstacle representation. Roadmap methods for generating waypoints: Voronoi diagrams, probabilistic roadmaps, RRTs. Graph-search algorithms for dynamically computing the optimal sequence of waypoints. Optimal control and optimization approaches. Potential fields.

AI planning: Introduction to Markov Decision Processes (MDPs) and solutions based on dynamic programming and reinforcement learning. Deliberative vs reactive behaviour. Fundamental automated planning methods and algorithms (state machines, STRIPS). Hierarchical task networks (HTNs). Temporal models.

The course will also include one lecture with an introduction to the Robot Operating System (ROS).

Learning outcome

Knowledge: Detailed knowledge about path planning and AI planning. Be able to read and understand methods published in the literature and evaluate and compare these with methods used in practical systems. Skills: Design and implement path- and action planning systems for ships, underwater vehicles, and aerial vehicles. Be able to simulate fundamental path- and action planning approaches, and their main variations, on such systems, including a real-world small-scale mobile robot. Independent management of small R&D projects and contribute actively in larger projects. General competence: Communicate work related problems with specialists and nonspecialists.

Learning methods and activities

Lectures and mandatory computer assignments. The objectives of the assignments are to simulate and test self-developed path- and action planning methods for marine, ground and aerial vehicles. At least one algorithm will also be implemented on a real-world, small-scale mobile robot.

Compulsory assignments

  • Assignments

Further on evaluation

School exam in writing (80%) and one A-F graded mandatory assignment (20%) are the basis for the final grade in the subject. In addition, three mandatory pass/fail assignments must be delivered, but do not affect the grade. The final grade is given as a letter. The exam is only given in English but answers in both Norwegian and English are accepted. If there is a re-sit examination, the examination form may be changed from written to oral. The computer assignments, take-home project and final exam must all be passed in order to pass the course. In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety.

Required previous knowledge

TTK4105 Control Systems, alternatively TTK4230 Control Systems or equivalent. TTK4130, Modelling and simulation. TTK4135, Optimization and control.

Course materials

  • LaValle, Steven M. Planning algorithms. Cambridge university press, 2006.
  • Lekkas A.M. Lecture notes on path- and action planning, 2022.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2025

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Engineering Cybernetics
  • MSc-level Engineering and Architecture
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Engineering Cybernetics

Timetable

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Examination

Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD School exam 8/10 B 2025-05-19 15:00 INSPERA
Room Building Number of candidates
SL410 orange sone Sluppenvegen 14 22
Spring ORD Assignment 2/10
Room Building Number of candidates
Summer UTS School exam 8/10 B INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

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