This assessment will consist of problems that require you to implement software using the Robotic Operating System (ROS) and the Python programming language. You are expected to learn the basics of the Python programming language and the ROS framework during the first two weeks of the course. Interactive software tutorials will be provided using ROS to help you gain hands-on experience, and the assessment items will be extensions of these tutorials. Therefore, you are required to complete the interactive tutorials before attempting the assessment items.

The assessment questions and marking criteria will be available on the Moodle course page. This assessment will test your understanding of coordinate system transformations, mathematical modelling of robotic manipulators, and trajectory generation. You are required to demonstrate your understanding by developing robotic models in ROS simulation environments and generating trajectories using the Python programming language.

Your final submission must include the software codes, the simulation outputs, video demonstrations, and a report.

Minimum mark requirement: You must achieve at least 30% for this assessment.
This assessment uses the University’s 72‑hour grace period after the deadline; no late penalty applies within that window.

AI ASSESSMENT SCALE - AI COLLABORATION
You may use AI to assist with specific tasks such as drafting text, refining, and evaluating your work. You must critically evaluate and modify any AI-generated content you use.

To obtain full marks for this assessment, you must satisfy the following requirements:

1. Your computer code must be appropriately structured, properly commented, and demonstrate relevant coding practices.
2. The mathematical models you develop must be accurate and produce logically justified results.
3. Your computer code must execute without compilation or runtime errors.
4. The software output must be consistent with the explanations provided in the report and the simulation results included in the submission.
5. All workings and assumptions must be clearly presented.

For this assessment, you will be tested on your understanding of inverse kinematics and the application of machine-learning models for object detection. You will also be required to develop mathematical models for multi-link robotic manipulators and create simulation models using the Robotic Operating System (ROS) framework. In addition, you will be expected to create an image dataset and train the YOLO deep learning network for object detection.

To complete this assignment, you will need a strong understanding of advanced ROS concepts. Weekly interactive tutorials will cover the required topics and provide relevant code samples to support your learning. You must also prepare a report that includes code outputs, explanations, and simulation results.

Your final submission must include the software codes, the simulation outputs, video demonstrations, and a report.

Minimum mark requirement: You must achieve at least 50% for this assessment.
This assessment uses the University’s 72‑hour grace period after the deadline; no late penalty applies within that window.

AI ASSESSMENT SCALE - AI COLLABORATION
You may use AI to assist with specific tasks such as drafting text, refining, and evaluating your work. You must critically evaluate and modify any AI-generated content you use.

To obtain full marks for this assessment, you must satisfy the following requirements:

1. Your computer code must be appropriately structured, properly commented, and demonstrate relevant coding practices.
2. The mathematical models you develop must be accurate and produce logically justified results.
3. Your computer code must execute without compilation or runtime errors.
4. The software output must be consistent with the explanations provided in the report and the simulation results included in the submission.
5. All workings and assumptions must be clearly presented.
    

This assessment consists of computer laboratory sessions and practical activities with robots and is divided into four laboratory assessments (Labs 1 to 4). You are required to use the specified software and simulation environment to complete each lab. Most labs can be completed within the simulation environment; however, you must attend the mandatory laboratory sessions that involve direct robot interaction.

Details of these labs and practical activities will be available on the unit Moodle website. The laboratory and practical components are compulsory, and you must pass them in order to pass the unit. All students are required to complete the labs during the compulsory residential school. Laboratory reports must be submitted individually, and team reports will not be accepted.

Minimum mark requirement: You must achieve at least 50% for this assessment.
This assessment uses the 72‑hour grace period for submissions; however, attendance at scheduled in‑person lab sessions is mandatory and cannot be deferred

AI ASSESSMENT SCALE - AI COLLABORATION
You may use AI to assist with specific tasks such as drafting text, refining, and evaluating your work. You must critically evaluate and modify any AI-generated content you use.

To obtain full marks for this assessment, you must satisfy the following requirements:

1. You must provide correct answers, including relevant plots and figures where appropriate.
2. Your code must be readable, well-structured, neat, and clearly organised. 
3. You must properly comment and appropriately format your computer code.
4. Your computer code must run without compilation or execution errors.
5. Your software output must be consistent with the explanations in your report and the simulation results included in your submission.
6. You must clearly show all workings and assumptions.

This is a project-based assignment that addresses a real-world challenge, where the project and its report form the primary assessment components. You are permitted to work in a group of two to three students. The project is task-based and requires your group to program robotic platforms to complete specified tasks, with marks awarded based on the successful completion of each task.

You are expected to commence your group project work in Week 5, with the final demonstration scheduled for Week 12. Each student must submit an individual report outlining their specific contributions; a single report per group will not be accepted. The project output must be demonstrated within a simulation environment, and the final codebase must be submitted to the assigned code repository. Peer evaluation will also be conducted to assess individual contributions within each group.

Minimum mark requirement: You must achieve at least 50% for this assessment.
This assessment uses the University’s 72‑hour grace period after the deadline; no late penalty applies within that window.

AI ASSESSMENT SCALE - AI COLLABORATION
You may use AI to assist with specific tasks such as drafting text, refining, and evaluating your work. You must critically evaluate and modify any AI-generated content you use.