Introduction to Vision and Robotics

In 2017/2018 the course will be taught in Semester 1 starting Sept 2017

Robotics and Vision applies AI techniques to the problem of making devices capable of interacting with the physical world. This includes moving around in the world (mobile robotics), moving things in the world (manipulation robotics), acquiring information by direct sensing of the world (e.g. machine vision) and, importantly, closing the loop by using sensing to control movement. This module introduces the basic concepts and methods in these areas and serves as an introduction to the more advanced robotics and vision modules.

Course Lecturers: 

Michael MistryTim Hospedales
Email: mmistry AT inf DOT ed DOT ac DOT uk Email: t DOT hospedales AT ed DOT ac DOT uk
Office: 1.22A Informatics Forum Office: 1.10 Informatics Forum

Other Personnel:

Support of Distance Learning Version of Course:

Schedule for Resident 3rd year Students:

The master timetable can be found in the 3rd year course catalogue.
Review Lectures: Two per week.

Supervised Lab Sessions: Appleton Tower 3.01.

Schedule for Distance Learning MSc Students:

This course will be simultaneously delivered to resident 3rd year informatics undergraduates and distance learning MSc students. Lecture videos are available online (see below). The review lectures will be streamed via the LEARN system allowing distrance students to ask questions (using 'Collaborate'). The assignments will follow the same schedule and approach as for the local course. Assignments will be remotely assessed at a convenient time for our demonstrators and the student.

Note: From 2017/18 the course will use free software. Distance students are no longer required to buy software/robot kit for the assignment.

Material specific to the Distance Learning course can be found here.

Inverted Classroom:

IMPORTANT INFORMATION: This course is not taught by the traditional lectures. Instead, IVR uses an Inverted Classroom method. This means that you will have about 15 hours of video to watch in your own time ('Lecture Videos'). This material is assessible. There are still 2 full class meetings each week ('Review Lectures'). We will discuss any questions that you either suggest in advance or raise in class on the day. Here is an Introduction to how the course is intended to be followed.

Lecture videos, associated readings and associated Matlab are hosted on the University's LEARN system. You will need an EASE account to access this materials. To access the materials:

Introductory Practical Labs

See the LEARN page.

Assessment:

See the LEARN page.

Exam (60%)
Here is a sample paper with sample answers.
The lecture and practical contents define the examinable material.


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