Master 2024/2025

Perception in Robotics

Type: Elective course (Math of Machine Learning)

When: 1 year, 2, 3 module

Open to: students of one campus

Language: English

Course Syllabus

Abstract

This course will present the fundamental theory and application of perception techniques. The word perception on the context of this course will refer to the problems of Localization, Mapping and in general State Estimation. Today we are witnessing an explosion on the applications for this technology, originally developed on the robotics field, being outsourced to other domains such as self-driving cars, augmented reality, flying drones, etc. Yet there are many challenges to be solved on a wide variety of research topics. The content of the course will be mainly based on a probabilistic approach to perception problems and will examine a selected set of contemporary algorithms in depth. Topics include Bayesian filtering; Batch Estimation, Mapping, localization and simultaneous localization and Mapping (SLAM); Observation and transition functions; Read below about the course policy, final project and other details.