49274 Space Robotics
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Subject handbook information prior to 2025 is available in the Archives.
Credit points: 6 cp
Subject level:
Postgraduate
Result type: Grade and marksRequisite(s): (120 credit points of completed study in spk(s): C10061 Bachelor of Engineering Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10066 Bachelor of Engineering Science OR 120 credit points of completed study in spk(s): C10067 Bachelor of Engineering OR 120 credit points of completed study in spk(s): C10062 Bachelor of Engineering Bachelor of Arts International Studies Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10063 Bachelor of Engineering Bachelor of Arts International Studies OR 120 credit points of completed study in spk(s): C10065 Bachelor of Engineering Bachelor of Business OR 120 credit points of completed study in spk(s): C10068 Bachelor of Engineering Bachelor of Business Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10073 Bachelor of Engineering Bachelor of Science OR 120 credit points of completed study in spk(s): C10074 Bachelor of Engineering Bachelor of Science Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10075 Bachelor of Engineering Bachelor of Medical Science OR 120 credit points of completed study in spk(s): C10076 Bachelor of Engineering Bachelor of Medical Science Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10078 Bachelor of Engineering Bachelor of Biotechnology OR 120 credit points of completed study in spk(s): C10079 Bachelor of Engineering Bachelor of Biotechnology Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C09067 Bachelor of Engineering (Honours) Diploma Professional Engineering Practice OR 120 credit points of completed study in spk(s): C09066 Bachelor of Engineering (Honours) OR 120 credit points of completed study in spk(s): C09069 Bachelor of Engineering (Honours) Bachelor of Arts International Studies Diploma Professional Engineering Practice OR 120 credit points of completed study in spk(s): C09068 Bachelor of Engineering (Honours) Bachelor of Arts International Studies OR 120 credit points of completed study in spk(s): C09070 Bachelor of Engineering (Honours) Bachelor of Business OR 120 credit points of completed study in spk(s): C09071 Bachelor of Engineering (Honours) Bachelor of Business Diploma Professional Engineering Practice OR 120 credit points of completed study in spk(s): C09072 Bachelor of Engineering (Honours) Bachelor of Science OR 120 credit points of completed study in spk(s): C09073 Bachelor of Engineering (Honours) Bachelor of Science Diploma Professional Engineering Practice OR 120 credit points of completed study in spk(s): C09074 Bachelor of Engineering (Honours) Bachelor of Medical Science OR 120 credit points of completed study in spk(s): C09075 Bachelor of Engineering (Honours) Bachelor of Medical Science Diploma Professional Engineering Practice) AND (48430 Fundamentals of C Programming OR 48623 Mechatronics 2 OR 41012 Programming for Mechatronic Systems)
These requisites may not apply to students in certain courses. See access conditions.
Description
This subject presents a broad overview of the technologies associated with robotics for space environments and related applications of modern robotic systems. Major topics covered are sensing, mapping, navigation, path planning and coordination of robots in planetary and microgravity settings. The subject consists of a series of classes on robot fundamentals and case studies on practical robot systems. Material covered in classes are illustrated through laboratory assignments and a group project. The objective of the subject is to provide students with the essential skills necessary to be able to develop robotic systems for particular space applications and related broader contexts.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Analyse problems in mobile robot applications to successfully prototype advanced robotic systems. (C.1) |
|---|---|
| 2. | Apply algorithms to simulate and implement in software systems for practical application. (D.1) |
| 3. | Demonstrate an understanding of conceptual principles related to sensors, actuators, and control techniques in modern robotic systems. (D.1) |
| 4. | Demonstrate effective project management of tasks within active collaboration of a project team. (E.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- 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.
- 2.1. Application of established engineering methods to complex engineering problem solving.
- 2.2. Fluent application of engineering techniques, tools and resources.
- 3.2. Effective oral and written communication in professional and lay domains.
Teaching and learning strategies
Student learning in this subject is facilitated through a combination of online video lectures, seminars, small in-class team work, computer laboratories, and a practical group project. Topic notes and videos are used to introduce students to the key fundamental concepts and their interrelations. Face-to-face class time is divided into two parts: there is a 1.5-hour interactive seminar-style activity followed by a 1.5-hour tutorial-style activity per week.
Students are expected to read the topic notes and watch the Canvas videos before coming to the classes which inform class discussions. The seminar portion of class time will discuss the major issues and questions raised from the students regarding different topics on mobile robotics and the application in space domains and broader contexts. The tutorial portion of class time will involve students forming small groups to work on appropriate tutorial-style problems which help to motivate, illustrate and exemplify the concepts presented in the topic notes and video lectures. Academic staff will facilitate group and whole-of-class discussions on selected problems, with the aim of illustrating techniques and providing immediate feedback on problem-solving processes. Some class time also occurs in computer labs where students are introduced to the Robotic Operating Systems which is used in industry and research work.
A team project is undertaken by students so that they apply the learned robotics methodologies to a practical application motivated by space robotics systems. Each team submits a technical report and makes an oral presentation on their mobile robotic system, to give students practice in communicating technical ideas.
Students are provided feedback to gauge their learning progress throughout the session. Students use feedback to make improvements to the next iterations of their designs and implementations. The face-to-face time is used to provide immediate verbal feedback, whilst written feedback is provided on written assessment tasks. Students also receive verbal feedback from their peers whilst undertaking the team project.
Content (topics)
The objective of the subject is to provide students with the essential skills necessary to develop software for robotic systems in practical space applications. Space Robotics builds on and brings together the concepts of Mechatronic Systems, Sensors and Control, and Object-oriented Programming in a space engineering context. It is intended to provide students with comprehensive hands-on experience in system design.
Subject matter discussed in this course includes:
- Sensing and perception for localisation in terrestrial environments
- Path planning and traversability analysis in planetary exploration
- Semi-automation / full automation to allow command and control in reduced bandwidth environments for autonomous surface operations
These concepts will be demonstrated on real data from planetary-like environments and simulated space environments. The unit of study will include a major project, where groups of students design and develop a complex robotics system.
Assessment
Assessment task 1: Localisation of a Mobile Robot
| Intent: | To develop and demonstrate proficient skills in designing, implementing, and testing software for applying robot localisation algorithms. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Laboratory/practical |
| Groupwork: | Individual |
| Weight: | 15% |
Assessment task 2: Path Planning for a Mobile Robot
| Intent: | To develop and demonstrate proficient skills in designing, implementing, and testing software for applying robot path planning algorithms. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Laboratory/practical |
| Groupwork: | Individual |
| Weight: | 15% |
Assessment task 3: Project Demonstration
| Intent: | Demonstrate capability to design and implement algorithms within a complex software system to meet set requirements of project specifications. |
|---|---|
| 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): C.1, D.1 and E.1 |
| Type: | Presentation |
| Groupwork: | Group, group and individually assessed |
| Weight: | 30% |
Assessment task 4: Project Documentation
| Intent: | Demonstrate formal report writing skills that include methodology, implementation, and experimental results based on the team project, as well as an understanding of important techniques in advanced robotic systems |
|---|---|
| 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): C.1, D.1 and E.1 |
| Type: | Report |
| Groupwork: | Group, group and individually assessed |
| Weight: | 15% |
Assessment task 5: Exam
| Intent: | Demonstrate a deep understanding of fundamental concepts and algorithms that are essential components of advanced robotic systems designed for space applications and broader contexts. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 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: | 25% |
| Length: | Exam length: 90 minutes as an online quiz through Canvas during a specified time window |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.
Recommended texts
There is no textbook for this subject, but there are a few important references listed below.
References
- S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics, MIT Press, 2005.
- S. M. LaValle. Planning Algorithms. Cambridge University Press, 2006.
- P. Corke, Robotics, Vision and Control: Fundamental Algorithms in Python. Springer Nature, 2023.
- Python: https://docs.python.org/2/tutorial/index.html
- Robot Operating System (ROS): https://wiki.ros.org/ROS/Introduction
Other resources
This subject will make use of Canvas as an alternative means of communication between teaching staff and students. Many of your other subjects will be using Canvas to a greater or lesser extent than we will be in this subject. You should be registered automatically if you have enrolled correctly. We will be posting announcements and making use of the broadcast email facility to provide you with information and notices as necessary.
If you have any trouble with Canvas you should first contact the ITD helpdesk on x2222 or help.desk@uts.edu.au.
Canvas: http://canvas.uts.edu.au/