University of Technology Sydney

42043 Robotics Studio 1

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2020 is available in the Archives.

UTS: Engineering: Mechanical and Mechatronic Engineering
Credit points: 12 cp

Subject level:

Postgraduate

Result type: Grade and marks

There are course requisites for this subject. See access conditions.

Description

This is a studio subject. It is not a conventional subject guided by a set curriculum. Its purpose is to provide an environment in which students can gain and simultaneously translate knowledge into a robotics system. Studios are product-based subjects, largely conducted in the studio, in collaboration with other students, academic staff and industry mentors. Students do a combination of individual self-directed study and project work.

This is the first studio in the fundamentals stage of the Robotics Engineering major. The major has three studios situated in the following stages: fundamentals; applications; and professional. The stages of the projects are the means by which students learn how to apply their knowledge to what they can achieve. The stages follow the classic engineering paradigm of assess, design and implement.

The objective of this studio is to introduce students to the multidisciplinary field of robotics engineering in both theory and practice. It aims to familiarise students with the robotics topics of mathematics, hardware and software, control and planning, sensing and perception motivated by real-world applications. Individual tasks in this studio are guided by a learning contract established at the beginning of the session.

What differentiates the applications studio from the fundamentals studio is the expectation of the level of proficiency of students. Once students have completed the fundamentals and applications studios and a range of coursework subjects, it is expected that they have the skills and knowledge to allow them to undertake the development of more challenging products in the final studio.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Engage with stakeholders to identify a problem
2. Apply design thinking to respond to a defined or newly identified problem
3. Apply technical skills to develop, model and/or evaluate design
4. Demonstrate effective collaboration
5. Conduct critical self and peer review and performance evaluation
6. Gain an overview of the established technologies associated with industrial robots and the components that make up a robotic system
7. Gain an understanding of the traditional principles of operation of robot motion systems, such as conventions used in robot kinematics and dynamics frames of reference or basic control strategies
8. Be familiar with trajectory planning and control of industry robots for different applications
9. Examine advanced topics in robotics that deal with collision avoidance and optimization for robot trajectory planning and control

Course intended learning outcomes (CILOs)

This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):

  • Socially Responsible: FEIT graduates identify, engage, and influence stakeholders, and apply expert judgment establishing and managing constraints, conflicts and uncertainties within a hazards and risk framework to define system requirements and interactivity. (B.1)
  • Design Oriented: FEIT graduates apply problem solving, design thinking and decision-making methodologies in new contexts or to novel problems, to explore, test, analyse and synthesise complex ideas, theories or concepts. (C.1)
  • Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
  • Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating autonomously within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)

Teaching and learning strategies

The Robotics Studio provides technical rationale and application in the first part of the semester. In the second part of the semester, students apply their understanding to product development.

In the first five weeks of the studio students are provided an opportunity to review and expand their fundamental knowledge through a combination of online content and in-class activities. Students are expected to have completed pre-class activities, such as watching lecture videos / running provided simulations and completing programming challenges, so that they are well prepared for the in-class activities that reinforce these concepts through a series of collaborative problem solving exercises. Students demonstrate that they have developed the required understanding of these basic competencies on an individual level through a series of quizzes. Quizzes are practical hands-on activities, and require completion of portions of code to achieve certain expected basic functions, submission of quizzes is via GIT and/or UTS online. The quizzes inform level of understanding to prepare for product development. Individual student feedback from staff is provided on each quiz and during formation of the ILC.

Students formalise the product development carried out in the studio through an individual learning contract (ILC). The product must demonstrate application of the programming, sensing and control competencies. The ILC is developed in collaboration with subject coordinator, who acts as a stakeholder as well as a mentor. The ILC needs to stipulate the iterative product development lifecycle and application of agile methodologies. As part of iterative process students have the opportunity to revisit the ILC during the session if required. Student progress is demonstrated through the Personal Design Journal which is audited weekly, code sprints with in-class demonstration and the peer teaching activity. Staff and peer feedback are provided during in-class demonstration of code sprint and the peer teaching activity. The final product will be demonstrated in class.

Studio learning is a shared learning opportunity; collectively we are responsible for translating fundamental robotic competencies, programming, sensing and control, to the process of product development. Assistance is readily provided in-class while online collaborative platform Slack is leveraged for ongoing support. Students are especially encouraged to leverage the digital space to collaboratively exchange ideas and share technical insights.

Content (topics)

The following topics will be covered:

Robotic maths

  • 2D transforms
  • basic filtering
  • basic probability

Software and hardware

  • Basic C++ in ROS (in Linux)
  • basic Matlab
  • basic designs
  • version control
  • documentation (doxygen, wiki)

Planning and Control

  • Basic planning 2D
  • low level control

Sensing and Perception

  • Laser range finder (modeling, noise)
  • 2D basic mapping
  • basic localization

Basic research project skills

Assessment

Assessment task 1: Review Quizzes

Intent:

Test the student’s knowledge of programming, sensing and control in an incremental manner. Provide feedback to students throughout the session.

Objective(s):

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

D.1

Type: Quiz/test
Groupwork: Individual
Weight: 20%

Assessment task 2: Individual Learning Contract Agreement

Intent:

Creation of an Individual Learning Contract allows students to identify and document their learning direction, and set goals for the session.

Objective(s):

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

E.1

Type: Portfolio
Groupwork: Individual
Weight: 5%

Assessment task 3: Individual Learning Contract Finalisation

Intent:

Creation of an Individual Learning Contract allows students to identify and document their learning direction, and set goals for the session.

Objective(s):

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

E.1

Type: Portfolio
Groupwork: Individual
Weight: 35%

Assessment task 4: Project Demonstration / Delivery

Intent:

Students demonstrate their ability to deliver a Product or Prototype to an agreed scope. In doing so, students also demonstrate their capacity to solve problems, create solutions, work with teams, communicate professionally, and manage time and tasks.

Objective(s):

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

B.1, C.1, D.1 and E.1

Type: Project
Groupwork: Individual
Weight: 30%

Assessment task 5: Personal Design Journal

Intent:

Creation of a Personal Design Journal that allows each student to record and reflect on their process and experiences in completing both their Individual Learning Contract as well as their project (product) journey.

Objective(s):

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

B.1, C.1, D.1 and E.1

Type: Journal
Groupwork: Individual
Weight: 10%

Minimum requirements

In order to pass the subject, a student must achieve an overall mark of 50% or more.

References

Programming for Mechatronic Systems

[1] Elliot B. Koffman & Paul A.T. Wolfgang, Objects, Abstraction, Data Structures and Design Using C++, John Wiley & Sons, Inc
ISBN 0-471-46755-3

[2] Roberts, E.,Programming abstractions in C++, Pearson, 2014

[3] D. Ryan Stephens; Christopher Diggins; Jonathan Turkanis, Jeff Cogswell, C++ Cookbook, O'Reilly Media, Inc., 2005

[4] Lippman, Stanley B, C++ primer, Addison-Wesley, 2005

Sensors and Control

[1] Nixon, Mark S, Feature extraction & image processing for computer vision, Oxford : Academic, 2012

[2] Introduction to Sensors for Ranging and Imaging by Graham Brooker, Sci Tech Publishing Inc., 2009

[3] Image Processing Toolbox, https://au.mathworks.com/products/image.html

[4] Image Acquisition Toolbox, https://au.mathworks.com/products/imaq.html

[5] Camera Calibration Toolbox, http://www.vision.caltech.edu/bouguetj/calib_doc/

[6] Katsuhiko Ogata, Modern Control Engineering, (3rd Edition)

[7] Jefferey B. Burl, Linear Optimal Control, Addison Wesley.

[8] Control Tutorial for MATLAB, http://www.engin.umich.edu/group/ctm/state/state.html

[9] J.M. MacIejowski, Multivariable Feedback Design, Addison-Wesley, 1989

[10] Branislav Kisacanin, Gyan C. Agarwal, Linear Control Systems: With Solved Problems and MATLAB Examples

[11] Control system toolbox, http://www.mathworks.com/products/control/

[12] Katsuhiko Ogata, Discrete-Time Control Systems (2nd Edition)