Part A: Course Overview
Course Title: Programming Autonomous Robots
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
COSC2814 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 1 2021 |
COSC2814 |
City Campus |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Sem 1 2022, Sem 1 2023, Sem 1 2024, Sem 1 2025 |
COSC3070 |
RMIT University Vietnam |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Viet1 2025 |
COSC3071 |
RMIT Vietnam Hanoi Campus |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Viet1 2025 |
Course Coordinator: Dr Timothy Wiley
Course Coordinator Phone: +61 3 9925 5202
Course Coordinator Email: timothy.wiley@rmit.edu.au
Course Coordinator Location: 14.11.13
Course Coordinator Availability: By appointment, by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
Enforced Pre-Requisite Courses
Successful completion of the following course/s:
Note: it is a condition of enrolment at RMIT that you accept responsibility for ensuring that you have completed the prerequisite/s and agree to concurrently enrol in co-requisite courses before enrolling in a course.
For information go to RMIT Course Requisites webpage.
Course Description
Software for robots face unique challenges, especially semi or fully automated robotic systems. This software must handle the limited computation power of robots along with the uncertainty and noise produced by their sensors and actuators. Robotic software must integrate across algorithms at multiple levels of abstraction, from the low-level information of the sensor’s, to high-level reasoning. This course focuses on the design and development of the software modules and architectures for autonomous robotic systems, including reactive actuator control, localisation, mapping, vision and audio processing, and task planning. You will complete practical work both in simulation and on real-world robot platforms.
This course is taught in parallel with COSC2781 (PG)
Objectives/Learning Outcomes/Capability Development
Program Learning Outcomes
This course is an option course so it is not required to contribute to the development of program learning outcomes (PLOs) though it may assist your achievement of several PLOs.
For more information on the program learning outcomes for your program, please see the program guide.
Upon successful completion of this course you should be able to:
- Discuss and Critically Analyse and a variety of software architectures and algorithms for solving typical problems in the context of autonomous robot systems; Discuss and Critically Analyse the strengths and limitations of these architectures and algorithms.
- Discuss and Critically Analyse the challenges of designing and developing software for a variety of robot systems of different complexities, including noise, uncertainty, and computational power.
- Research, Discuss, and Use new and novel algorithms for solving problems with autonomous robot systems.
- Use pre-existing robot software to solve common problems on simulated and real-world robots; Develop and Implemented new algorithms and software for solving problems on simulated and real-world robots; Integrate this software in the ROS framework.
- Develop skills for further self-directed learning in the general context of software, algorithms, and architectures for autonomous robot systems; Adapt experience and knowledge to and from other computer sciences contexts such as artificial intelligence, machine learning, and software design.
Overview of Learning Activities
You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.
You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.
Overview of Learning Resources
You will make extensive use of computer laboratories, and relevant robot hardware and software provided by the School. You will work in the Artificial Intelligence Innovation Lab and be required to adhere to relevant health and safety requirements. You will be able to access course information and learning materials through MyRMIT and may be provided with copies of additional materials in class or via email. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.
Overview of Assessment
This course has no hurdle requirements.
Assessment tasks
Assessment Task 1: Group assessment
Weighting: 25%
This task supports CLOs: 1, 2, 4
Assessment Task 2: Major project and Group assessment
Weighting: 50%
This task supports CLOs: 1, 2, 3, 4, 5
Research Presentation: Research Presentation
Weighting: 25%
This task supports CLOs: 1, 2, 3, 5
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.