COM00186M Autonomous Robotic Systems Engineering (AURO) Coursework 2025-26 | UoY

COM00186M Task Definition

This assessment focuses on the retrieval of items by autonomous mobile robot(s). You will be provided with a simulated world containing items distributed throughout the environment, which the robot(s) must collect and return to a home zone. This simulated world will also contain obstacles that the robot(s) need to avoid.

A robot can collect an item by driving into it, and will ‘hold’ the item until it has returned to the home zone. A robot cannot hold more than one item at a time. Once an item has been collected and returned home, a new one will automatically spawn to replace it.

You must design and implement a solution to this task, using mobile robot(s) that autonomously collect the items and return them home in an efficient manner.

Deliverables

This assessment is worth 100% of the module mark, and is made up of 3 parts with the following weightings:

1. Implementation: 40%
2. Demonstration: 10%
3. Report: 50%

Guidance on what you are required to do for each part of the assessment is provided in the following sub-sections. A full marking rubric can be found in Section 4.

Implementation (40%)

You should engineer an autonomous robotic system that solves the assessment task efficiently, while obeying the following constraints:

• You must implement your solution in simulation, using the Robot Operating System (ROS). Specifically, you must use ROS 2 Humble Hawksbill, Gazebo Classic 11, and the Python client library rclpy.
• You must use autonomously controlled (i.e. not teleoperated) TurtleBot3 Waffle Pi robot(s). Your solution may use up to 3 robot(s), and they must all start in the home zone.
• You must include a README file that describes how to run your code, and details any packages or environment variables that your implementation depends upon.

There are many different ways of approaching the assessment task, so there is scope for a variety of solutions. Your implementation will be assessed against the following criteria:

Sophistication [12 marks]: You will be assessed on the intelligence of your autonomous robotic system and how efficiently it addresses different aspects of the task. Multi-robot systems may be considered more sophisticated than single-robot systems, but only if they are implemented appropriately.

System architecture [12 marks]: The architecture of your autonomous robotic system will depend upon your approach to the assessment task. You will be assessed on the modularity of your solution – i.e. how well it separates functionality into reusable components with appropriate interfaces between them.

Use of ROS concepts [8 marks]: Your solution should use a variety of ROS concepts. You will be assessed on the breadth of the ROS features that your implementation uses, and how well you have demonstrated your understanding of them (through correct usage).

Understandability [8 marks]: Your implementation should be easy to understand. You will be assessed on the structure of your code, use of sensible naming conventions and comments, and how comprehensive your README file is.

You will be provided with code that defines the assessment task, which should be downloaded from the VLE. This code sets up the simulated world and runs a ROS node that spawns items and keeps track of when they are collected and returned home by the robot(s). You will also be provided with a ROS node that processes images from a robot’s camera and publishes information about any items that are detected. You must use this code without modification, as it defines the assessment parameters of the task.

You are allowed to use any of the example code provided as part of the teaching delivery for the AURO module, including solutions to practical exercises. The use of 3rd party packages is also permitted, as long as you cite the source and include instructions on how to build them.

Demonstration (10%)

You must demonstrate your solution by recording a video that showcases its features, as well as its performance with respect to the assessment task.

• Your video should be a screen recording that demonstrates the operation of your autonomous robotic solution in both the Gazebo simulator and the RViz visualisation tool.
• You should not show your code (this will be assessed separately), but you should show the terminal commands used to run your solution.
• You must provide captions that explain what is being shown in your video as it progresses.

The video demonstration is worth [10 marks]. You will be assessed based on how well the video demonstrates your implementation and how informative the associated captions are. The purpose of this video is only to demonstrate that your solution performs as described in your report. You do not need to include any discussion, analysis, or evaluation in this video – this should be included in your report instead.

Your video must be no longer than 5 minutes in duration. If your video exceeds this time limit, the marker will stop watching after 5 minutes, and base the mark on what they have seen so far.

Report (50%)

You must write a report that details the design and implementation of your solution. You should also analyse the performance of your solution, and present the results in your report. Finally, your report should evaluate the strengths and weaknesses of your solution, and reflect on related safety implications and ethical considerations. The report must be structured as follows:

Design [8 marks]: This section should describe the design of your system and justify your design decisions. It should also include a diagram that communicates the high-level design of your system, and how the individual components interact (e.g. a block diagram).

Implementation [7 marks]: This section should describe and justify your implementation, with particular reference to your use of ROS concepts. It should also include a diagram that communicates how your solution achieves autonomy (e.g. a state machine). You should not include your code here, as this will be assessed separately.

Analysis [10 marks]: In this section, you should describe and justify your experimental approach to analysis. You should then present and interpret the results of your analysis, which should be both qualitative and quantitative. You may wish to present your data in the form of figures and/or tables.

Evaluation [10 marks]: This section should include a discussion of the strengths and weaknesses of your solution. Your evaluation should be based on your design, implementation, and analysis. It should also include a discussion of how well your solution would transfer from simulation to reality, and how this could be improved. You should further provide a critical analysis of the strengths and weaknesses of your solution, and relate this analysis to the academic literature.

Safety and ethics [10 marks]: This section should include a discussion of safety implications and ethical considerations related to item retrieval by autonomous robotic systems in real-world scenarios. You should also reflect on how these topics would relate to the approach taken by your solution, if it were to be implemented in a real-world scenario. You should further provide a critical analysis of these safety implications and ethical considerations, with reference to the academic literature.

The remaining [5 marks] of the report mark will be based on its presentation (structure, figures, adherence to the template, and use of referencing).

Your report must be formatted using the IEEE conference template (either LaTeX or Microsoft Word) 1, and any references must follow the IEEE referencing style2. You must use A4 paper size (not US letter, which is the default for the LaTeX template), and you must not edit the formatting (e.g. font, margins, columns).

You should not include an abstract, introduction, literature review, or any keywords. You should only include your examination number in the author field – do not include your name, username, email address, or any other identifying information. You should also include the module code COM00186M on the first page.

Your report must be no longer than 6 pages (excluding references). If your report exceeds this page limit, the marker will stop reading when they reach the limit, and base the mark on what they have read so far.

Submission

The submission of your implementation, demonstration, and report for this assessment should abide by the following rules.

Anonymity

You should identify yourself only by your examination number. Your name, username, email address, or any other identifying information must not be present anywhere in your submission.

This includes all ROS package metadata, code comments, environment variables, Linux terminal prompts, PDF metadata, video captions, etc. You must not narrate your video demonstration, nor include any audio or visuals that could deanonymise your submission.

Electronic submission

You should combine all of the files for your implementation, demonstration, and report into a single ZIP file and submit it via the Teaching Portal. The contents of this ZIP file should be structured as shown in Figure 1:

It is your responsibility to ensure that your implementation runs under the Departmental ROS environment before submission.

The source code of your implementation should be included in a directory called src containing your ROS packages. You should not include your entire ROS workspace – i.e. you should exclude the build, install, and log directories created by colcon.

Your README file should be in plain text format. You should also include a PNG file exported from rqt_graph that shows the ROS graph of your solution.

Your demonstration video must be in MP4 format, and the captions must be in SRT (SubRip) format.
Your report must be a single PDF file.

Marking rubric

The marking rubric for each part of the assessment is given below in the following tables:

1. Implementation (40%): Table 1 (pages 8 to 9)
2. Demonstration (10%): Table 2 (page 9)
3. Report (50%): Table 3 (pages 9 to 12)

Table 1: Implementation (40%)

Table 1: Implementation (40%) – Continued from previous page

Table 2: Demonstration (10%)

Table 3: Report (50%)

Table 3: Report (50%) – Continued from previous page