Advanced Robotics

ARO: Course Contacts

flittlet — Thu, 03 Aug 2023 14:55:09 +0000

ARO: Course Contacts flittlet Thu, 03/08/2023 - 15:55

Name	Role(s)	Email	Office (Phone)
Steve Tonneau	Course Organiser Tutor	stonneau@exseed.ed.ac.uk	BC-1.16
Ciarán Johnson	Demonstrator Marker	s1654111@sms.ed.ac.uk
Jonathan Gustafsson Frennert	Demonstrator [II]	s1915791@sms.ed.ac.uk
Ram Ramamoorthy	Course Lecturer	s.ramamoorthy@ed.ac.uk	IF-1.41 (505119)
Ciarán Johnson	Demonstrator Marker	s1654111@sms.ed.ac.uk
Ana Deligny	Marker	adeligny@ed.ac.uk
Peter Fagan	Teaching Assistant	s2456316@sms.ed.ac.uk	IF-1.38

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ARO: Assessment

flittlet — Thu, 03 Aug 2023 14:55:04 +0000

ARO: Assessment flittlet Thu, 03/08/2023 - 15:55

All coursework deadlines are avaible on learn (login required), directly through this link.

Coursework 1 is available here.

The solution is here
Deadline is end of week 5 (October 20th, 12:00 - to be clear: noon)
You need to submit your file in the form of a PDF through learn on time.

The instructions for the 15 points coursework 2 are here.

The instructions for the 25 points coursework 3 are here

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ARO: Resource List

flittlet — Thu, 03 Aug 2023 14:54:59 +0000

ARO: Resource List flittlet Thu, 03/08/2023 - 15:54

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ARO: Software Labs

flittlet — Thu, 03 Aug 2023 14:54:58 +0000

ARO: Software Labs flittlet Thu, 03/08/2023 - 15:54

Overview

Practical times

AT 3.01 - Tuesdays: 13:10 - 14:00 or 14:10 - 15:00 from week 3 to week 10.

Instructions

All instructions for the software lab are on this github page

https://github.com/ediaro23/lab

Software practical marking scheme

The practical marking scheme:

Coursework 2: lab report - 15 pt
Coursework 3: lab demo (3 sub-tasks) - 25 pt

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ARO: Tutorials

flittlet — Thu, 03 Aug 2023 14:54:57 +0000

ARO: Tutorials flittlet Thu, 03/08/2023 - 15:54

Tutorials (Robotics Algorithms)

Overview

The tutorial sessions focus on practical implementations of some of the algorithms discussed in the lecture.
Each week, the implementation of one algorithm is introduced and practiced. The code used can be found in the tutorial plan below.

Live python/code tutorials

Mondays: 15:10 - 16:00 or 16:00 - 16:10 week 2 - week 7. AT 3.01

!!! Important note: before coming to the first tutorial on week 2. you should:

make sure you are familiar with python (see tutorial 0 below)
have set up your DICE machine following the instructions on:
- https://github.com/ediaro23/tutorials

Tutorial plan:

TBA

Week	Date	Tutorial
1	before 25/09/23 (self taught)	Setup your working environment following the Readme on github on a DICE machine. You can choose to work on your own computer but we won't support any other system than Ubuntu 20.04 If you need a refresher on python, check out this video that demonstrates the setup (from 14 min). The material is available here, along with the slides.
2
3
4
5
6

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ARO: Guest Lectures

flittlet — Thu, 03 Aug 2023 14:54:57 +0000

ARO: Guest Lectures flittlet Thu, 03/08/2023 - 15:54

TBD

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ARO: Lectures

flittlet — Thu, 03 Aug 2023 14:54:56 +0000

ARO: Lectures flittlet Thu, 03/08/2023 - 15:54

Lecture Plan.

Week	Date	Lecture notes	Lecturer	Lecture topic
11	27 nov 2023	Monday Lecture	Steve Tonneau	Revision lecture
10	20 nov 2023	Monday lecture	Subramanian Ramamoorthy	Reinforcement learning
7	30 oct 2023	Monday lecture part 1 and 2	Steve Tonneau	Introduction to optimal control and trajectory optimisation
6	23 oct 2023	Monday lecture part 1 and 2	Subramanian Ramamoorthy	control
5	16 oct 2023	Monday lecture part 1 and 2	Subramanian Ramamoorthy	Dynamics I
4	09 oct 2023	Monday lecture part 1 and 2 Code here	Steve Tonneau	Motion planning
3	02 oct 2023	Monday lecture here	Steve Tonneau	Forward and Inverse kinematics
2	24 sept 2023	Monday lecture here Tuesday lecture here lectures notes here	Steve Tonneau	Rigid transformations, kinematic tree, forward geometry More on SO(3) and its representations
1	18-Sep-2023	Link to the pdf of the whole class here Link to individual ppts: Course introduction Overview of robotics Why are we here	Subramanian Ramamoorthy / Steve Tonneau	Introduction and short overview of different sub-fields in robotics, elements of robotics and their related techniques. First lecture as a live coding exercise to demonstrate the tools used in the course and discuss the relevant concepts

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ARO: Course Materials

flittlet — Thu, 03 Aug 2023 14:54:56 +0000

ARO: Course Materials flittlet Thu, 03/08/2023 - 15:54

Lecture Recordings

All lecture recordings should be accessed via Learn; you will need to log in using your EASE account. (Learn provides you with access to any lecture recordings available for this course. You will need to select the "lecture recording" link once, before you can access any direct links to a lecture recording.)

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ARO: Advanced Robotics

flittlet — Thu, 03 Aug 2023 14:54:54 +0000

ARO: Advanced Robotics flittlet Thu, 03/08/2023 - 15:54

Welcome to Advanced Robotics

Hello, we are pleased to welcome you to Advanced Robotics.

This course will be a Masters degree level (also open to UG students) introduction to core areas in robotics: kinematics and dynamics of robots; robot control, robot control theories; motion planning; optimisation and a light touch of robot learning.

Lectures on these topics will be complemented by a practical that exercises knowledge of these techniques on a robot in the physics simulation, motivated by tasks such as manipulation. Particularly, in order to bridge the gap between lectures and the virtual lab sessions, the course also provides tutorials dedicated to the practice of programming and the implementation of algorithms -- a step-to-step guidance from the equations to code.

The aim of the course is to present a unified view of the field, culminating in a practical involving the development of an integrated robotic system that embodies the key elements of the major algorithmic techniques. NOTE: This is a 20 pt course, as opposed to the standard 10 pt courses since this covers two topics: robotics & control and a practical element.

Learning Outcomes

On successful completion of this course, you should be able to:

analyse the fundamental principles and the essential concepts in canonical robotics topics, evaluate the suitability and applicability of the algorithms given a robotics problem. Identify, propose and develop robotic solutions to solve practical robotic tasks
program and implement theoretical algorithms using common programming languages, and develop proficiency in debugging the code
use common robotics-related software, and use simulation tools to successfully set up robotic tasks and environments
write up and deliver a technical and scientific report, and demonstrate analytical and critical thinking to explain the positive and negative results of the tasks, and evaluate the performance by using quantifiable metrics
increase awareness of health and safety issues while working with real robotic systems, acquire knowledge of basic safety procedures of operating robotic and / or electronic systems, learn practical skills in using physical emergency devices and implementing software safety measures

Course Outline

This is a fast-paced course that starts with the fundamentals and then proceeds to go in-depth with core elements in robotics. The focused topics cover: kinematics, dynamics and control; digital control systems; optimisation, robot motion planning; and robot learning.

The aim of the course is to present essentials in robotics, articulated robots in particular, culminating in a robotic lab practical. The lab involves the development of an integrated robotic system which embodies the major algorithmic techniques used in real-world robotic applications. To bridge the lectures on algorithms and lab sessions, the course also provides tutorials dedicated to the practice of programming and the implementation of algorithms - from the equations to code.

Lectures on these topics will be complemented by labs that exercise knowledge of a cross section of these techniques, based on realistic tasks driven by real-world applications, such as dual-arm robot manipulation. The practical lab is done in pairs and carried out mostly in simulation, with a demonstration on the real robot at the end of the course.

If things go well another hardware lab will be run towards the end of the semester where the students will get to play with actual robot parts.

Schedules for lectures, tutorials and labs

Lectures
Lecture sessions, Monday 13:10 - 15:00, week 1 - week 10.

Additional lectures (guest lectures etc) on some Tuesdays 10:00 - 11:00. Announced during the semester in the weekly announcement.

For tutorials and labs, you need to work in pair and distribute yourselves evenly around the proposed slots.

Tutorials

Live sessions:
Mondays: 15:10 - 16:00 or 16:00 - 16:10 week 2 - week 7.

Labs (coursework 2 and 3)

Tuesdays: 13:10 - 14:00 or 14:10 - 15:00 from week 3 to week 10.

Hardware Labs

Thursdays: 10:00 - 11:00 or 11:10 - 12:00 from week 5 to week 9.

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Advanced Robotics

ARO: Course Contacts

ARO: Assessment

ARO: Resource List

ARO: Software Labs

Overview

Practical times

Instructions

Software practical marking scheme

The practical marking scheme:

ARO: Tutorials

Tutorials (Robotics Algorithms)

Overview

Live python/code tutorials

Tutorial plan:

ARO: Guest Lectures

ARO: Lectures

Lecture Plan.

ARO: Course Materials

Lecture Recordings

ARO: Advanced Robotics

Welcome to Advanced Robotics

Learning Outcomes

Course Outline

Schedules for lectures, tutorials and labs

Lectures Lecture sessions, Monday 13:10 - 15:00, week 1 - week 10.

Tutorials

Labs (coursework 2 and 3)

Hardware Labs

Lectures
Lecture sessions, Monday 13:10 - 15:00, week 1 - week 10.