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 2025 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, 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 Robotics major, and its objective is to introduce students to the multidisciplinary field of robotics engineering in both theory and practice. It aims to familiarise students with the topics of robotics motivated by real-world applications. This studio has two tracks that cover essential components of any robotic system: (a) hardware/software track and (b) sensing/perception track. Individual projects in this studio, designed to deepen particular skills, are guided by a learning contract.

Once students have completed the first studio 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 second Robotics studio.

Subject learning objectives (SLOs)

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

1. Apply stakeholder analysis to inform engagement with stakeholders to scope robotics problem. (B.1)
2. Apply design thinking approach to develop solution to a robotics problem. (C.1)
3. Analyse industrial robots and the components to optimize robot trajectory planning and control. (D.1)
4. Collaborate in teams to demonstrate application of the programming, sensing and control competencies of a robotic system. (E.1)
5. Evaluate contributions of self in the context of teamwork to meet project goals. (F.1)

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)

Contribution to the development of graduate attributes

Engineers Australia Stage 1 Competencies

Students enrolled in the Master of Professional Engineering should note that this subject contributes to the development of the following Engineers Australia Stage 1 competencies:

  • 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
  • 1.4. Discernment of knowledge development and research directions within the engineering discipline.
  • 1.5. Knowledge of engineering design practice and contextual factors impacting the engineering discipline.
  • 2.1. Application of established engineering methods to complex engineering problem solving.
  • 2.2. Fluent application of engineering techniques, tools and resources.
  • 2.3. Application of systematic engineering synthesis and design processes.
  • 3.3. Creative, innovative and pro-active demeanour.
  • 3.4. Professional use and management of information.
  • 3.5. Orderly management of self, and professional conduct.
  • 3.6. Effective team membership and team leadership.

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 Canvas. 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 addresses the following subject learning objectives (SLOs):

3

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: Project

Intent:

Students to apply sensing and control strategies to achieve an integrated solution to given specifications in a robotics system specification. 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, manage time and tasks.
Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

1, 2, 3 and 4

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: Group, group and individually assessed
Weight: 50%

Assessment task 3: Exam

Intent:

The aim of the final exam is to assess students' deeper knowledge gained through lectures, lab classes and projects..
Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

2 and 3

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

C.1 and D.1

Type: Examination
Groupwork: Individual
Weight: 30%

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)