This module is only for students on the BASc degree programme and comprises Term 1 of the module: ECON0002: Economics.

Module description

This module introduces student to literature in Dutch. We will not discuss this literature solely its national Flemish or Dutch context,...

Module description

This module introduces student to literature in Dutch. We will not discuss this literature solely its national Flemish or Dutch context, but we will also focus on the wordliness of literature in Dutch: the manner in which it intervenes and is embedded in a wider global context. We will reflect on questions how literature in Dutch represents the world and the movement from characters of the Low Countries across the globe, or ‘others’ coming to the Low Countries. As a method, we will adopt a postcolonial and decolonizing perspective. The course has thus the threefold aim to acquaint student with literature in Dutch, literary analysis and literary/critical theory.

 

Primary texts will be made available in English.

 

Primary texts may include (fragments of):

 

· Hafid Bouazza, Abdullah's Feet

· Louis Couperus, The Hidden Force 

· Maria Dermoût, The Ten Thousand Things 

· M. Februari, The Literary Circle

· Hella S. Haase, The Black Lake

· Tip Marugg, The Roar of Morning

· Multatuli, Max Havelaar

Aims:

Students will gain knowledge about robot real-time pose estimation and mapping, with an emphasis on the use of vision as a primary sensor for mapping...

Aims:

Students will gain knowledge about robot real-time pose estimation and mapping, with an emphasis on the use of vision as a primary sensor for mapping the environment. The module will provide students with an understanding and practical experience of how to combine information from satellite navigation and motion sensing systems, recover geometry from optical sensors and creating an environment map which a robot can use for navigation and motion planning.

Learning outcomes:

On successful completion of the module, a student will be able to:

Understand the fundamental techniques used for real-time estimation in linear and nonlinear systems.
	Understand how to formulate algorithms to fuse data from satellite and motion sensing systems to estimate robot position; 3.understand how to formulate mapping and localisation problems in which robots construct sparse maps of their environment.
	Understand how to use camera data to create 3D reconstructions of the environment.
	Programme with Matlab or Python or C++ Availability and prerequisites.
Content:

To navigate safely, robots need the ability to localize themselves autonomously using their onboard sensors. Potential tasks include the automatic 3D reconstruction of buildings, inspection and surveillance. This module will teach current techniques for 3D localization, mapping and navigation that are suitable for robotics covering the following topics:

Filtering techniques and data fusion.
	Motion estimation and mapping using Simultaneous Localisation and Mapping (SLAM) techniques.
	Non-linear minimization for 3D reconstruction using structure-from-motion.
Requisites:

To be eligible to select this module as an option or elective, a student must: (1) be registered on a programme and year of study for which it is formally available; and (2) have basic familiarity with MATLAB and C++ (as most of the coursework is carried out using these languages.)