151-0325-00L  Planning and Decision Making for Autonomous Robots

SemesterHerbstsemester 2021
DozierendeE. Frazzoli
Periodizitätjährlich wiederkehrende Veranstaltung


151-0325-00 VPlanning and Decision Making for Autonomous Robots2 Std.
Mi10:15-12:00HG E 3 »
E. Frazzoli
151-0325-00 UPlanning and Decision Making for Autonomous Robots1 Std.
Mi12:15-13:00HG F 1 »
E. Frazzoli


KurzbeschreibungPlanning safe and efficient motions for robots in complex environments, often shared with humans and other robots, is a difficult problem combining discrete and continuous mathematics, as well as probabilistic, game-theoretic, and learning aspects. This course will cover the algorithmic foundations of motion planning, with an eye to real-world implementation issues.
LernzielThe students will learn how to design and implement state-of-the-art algorithms for planning the motion of robots executing challenging tasks in complex environments.
InhaltDiscrete planning, shortest path problems. Planning under uncertainty. Game-theoretic planning. Geometric Representations. Configuration space. Grids, lattices, visibility graphs. Sampling-based methods. Potential and Navigation functions. Mathematical Programming. Local and global optimization, convex relaxations. Planning with limited information. Multi-agent Planning.
SkriptCourse notes and other education material will be provided for free in an electronic form.
LiteraturThere is no required textbook, but an excellent reference is Steve Lavalle's book on "Planning Algorithms."
Voraussetzungen / BesonderesStudents should have taken basic courses in optimization, control systems, probability theory, and should be familiar with basic programming (e.g., Python, and/or C/C++). Previous exposure to robotic systems is a definite advantage.
Geförderte KompetenzenGeförderte Kompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft


Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte4 KP
PrüfendeE. Frazzoli
RepetitionDie Leistungskontrolle wird in jeder Session angeboten. Die Repetition ist ohne erneute Belegung der Lerneinheit möglich.
Prüfungsmodusschriftlich 150 Minuten
Zusatzinformation zum PrüfungsmodusThere is a written final exam during the examination session, which covers all material taught during the course, i.e. the material presented during the lectures and corresponding problem sets, programming exercises, and recitations.
Additionally, there will be programming assignments, which are an optional learning task during the semester, requiring the students to understand and apply the lecture material. These contribute a maximum of 0.25 grade points to the final grade, but only if it helps to improve the final grade.
Hilfsmittel schriftlichOne sheet of A4 paper, front and back. Only handwritten material by the individual student is allowed --- no computer printouts or photocopies. (Preparing such a sheet would be an important part of the learning process.)
Diese Angaben können noch zu Semesterbeginn aktualisiert werden; verbindlich sind die Angaben auf dem Prüfungsplan.


Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.


Keine Informationen zu Gruppen vorhanden.


Keine zusätzlichen Belegungseinschränkungen vorhanden.

Angeboten in

Maschineningenieurwissenschaften MasterRobotics, Systems and ControlWInformation
Robotics, Systems and Control MasterKernfächerWInformation