49274 Space Robotics
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Subject handbook information prior to 2024 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 mobile robots. Major topics covered are sensing, mapping, navigation and control of mobile robots. The subject consists of a series of lectures on robot fundamentals and case studies on practical robot systems. Material covered in lectures is illustrated through laboratory assignments. The objective of the course is to provide students with the essential skills necessary to be able to develop robotic systems for practical applications.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Simulate and implement algorithms for mobile robots. (D.1) |
|---|---|
| 2. | Plan their time, manage their work, and be an active team member of a group project. (E.1) |
| 3. | Analyse problems in mobile robot applications and propose appropriate engineering solutions. (C.1) |
| 4. | Illustrate detailed knowledge of the software and hardware architecture through programming and design of a modern robotic system. (D.1) |
| 5. | Illustrate knowledge of sensors, actuators and control techniques through robotic applications. (D.1) |
| 6. | Prototype advanced robotics systems. (C.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 group 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. The seminar portion of class time will discuss the major issues and questions raised from the students regarding different topics on mobile robotics. 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 group project is undertaken by students so that they apply the learned robotics methodologies to a practical application. Each group submits a technical report and makes an oral presentation on their mobile robotic system, to give students practice in communicating technical ideas.
Written and verbal feedback, including low stakes assessment, is provided to students to gauge their learning progress throughout the session. 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 group project.
Content (topics)
The subject consists of a series of lectures on robot fundamentals and case studies on practical robot systems. Material covered in lectures is related to the group project. The objective of the course is to provide students with the essential skills necessary to develop robotic systems for practical applications.
Advanced Robotics builds on and brings together the concepts of Mechatronics, Embedded C, and Object-oriented Programming. It is intended to provide students with comprehensive hands on experience in system design.
Subject matter discussed in this course includes, sensing, control, data fusion, localisation and path planning. These concepts will be demonstrated through practical systems namely, iRobot iCreate, Pioneer, HOMER and Fetch. The unit of study will include a major project, where groups of students design and develop a complex robotics system.
Assessment
Assessment task 1: Kalman Filtering for Localization
| Intent: | For this task, the students need to demonstrate an understanding of Kalman filters and robot kinematics, then implement the Matlab codes for the localisation. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 3, 4 and 5 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: Plan a path for a mobile robot
| Intent: | For this task, the students need to to demonstrate the basic concepts of path-planning of a mobile robot and be able to implement the C++ codes of A* (A-star) algorithm using a pre-built map under the ROS environment. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 3, 4 and 5 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: | The intent is to implement various stagesof location of multiple objects in a previously mapped/unmapped environment. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 2, 3, 4, 5 and 6 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: | This task is the documentation of the project using a written report and a video presentation. Students can use the report and video to demonstrate their in-depth understanding of the project work as well as use them as part of their project portfolios for future career in robotics. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 3, 4 and 6 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Report |
| Groupwork: | Group, group and individually assessed |
| Weight: | 15% |
Assessment task 5: Exam
| Intent: | The intent is to allow students to demonstrate their understanding of fundamental concepts and algorithms in advanced robotics covered during the subject. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 3, 4 and 5 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% |
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
- An introduction to Mobile Robotics, by Stefan B. Williams and Gamini Dissanayake
- Robot Localization: An Introduction, by Shoudong Huang and Gamini Dissanayake
- T. Barfoot, State Estimation for Robotics, available at http://asrl.utias.utoronto.ca/~tdb/bib/barfoot_ser17.pdf
- S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics, MIT Press, 2005
- Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software, by Yaakov Bar-Shalom, et al.
- Bayesian Filtering for Location Estimation, by Dieter Fox, et al. available at http://rse-lab.cs.washington.edu/papers/bayes-filter-pervasive-03.pdf
- Path Planning http://planning.cs.uiuc.edu/
- OpenCV http://sourceforge.net/projects/opencvlibrary/
- “Mechatronics System Design (First edition)”, by Shetty and Kolk, Thomson-Engineering
- C++ tutorial http://www.cplusplus.com/doc/tutorial/
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/