Learning objectives
At the end of the course, students will be able to:
* Identify the advantages and disadvantages in the use of different sensors and their potential combinations, depending on the application and the environmental conditions;
* Critically determine strengths, limitations and constraints of different approaches to sensor and data fusion;
* Employ and deploy techniques and methods to combine signals from several different sensing modalities;
* Extract and leverage information from unimodal and multimodal data for environment interpretation;
* Design, test, and evaluate single-sensor and multi-sensor systems for vehicle perception.
Prerequisites
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Course unit content
The goal of the course is the analysis of fundamental and advanced aspects of 3D perception and data fusion towards the robust and accurate sensing and interpretation of a vehicle's environment, both from a theoretical and practical perspective.
To this end, the exploration of more classic approaches to sensor data analysis and integration will be augmented with the investigation of state-of-the-art solutions from the most recent scientific literature.
The main topics in a nutshell:
* Sensors for Mobile Autonomous Systems
* Single-Sensor 3D Perception
* Traditional Data Fusion
* Learning-based Data Fusion
* From Interpretation to Interpretability and Explainability
Full programme
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Bibliography
There won’t be a reference textbook, but slides and additional material (e.g. scientific papers) will be provided during the course.
Teaching methods
The theoretical aspects will be covered during the lectures and will also include student presentations; the technical aspects will be approached via a project consisting of a series of assignments.
Assessment methods and criteria
Students will be asked to present and discuss scientific papers on the topics covered by the course and to implement and present a project.
Both paper and project presentations will take place throughout the course’s lectures.
The final grade will reflect the performance in the paper presentations/discussions as well as in the assignments.
Other information
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