CSIP5202 AI for Mobile Robots Coursework 1 (Lab 6) Specification 2025/26 | DMU

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Category	Assignment	Subject	Computer Science
University	De Montfort University (DMU)	Module Title	CSIP5202 AI for Mobile Robots

Assessment Title	Coursework 1 (Lab 6)
Academic Year	2025/26

CSIP5202 Faculty of Technology Coursework Specification 2025/26

Module name:	AI for Mobile Robots
Module code:	CSIP5202
Title of the Assessment:	Coursework 1 (Lab 6)
This coursework item is: (delete as appropriate)					Summative
This summative coursework will be marked anonymously: (delete as appropriate)						No
The learning outcomes that are assessed by this coursework are: 1. Understanding the subject-specific issues relating to programming mobile robots 2. Understanding and being able to program using the basic architectures to control robots 3. Understanding and being able to program to execute navigation, sensor data analysis and actuator control for mobile robots
This coursework is: (delete as appropriate)				Individual

This coursework constitutes 44 % of the overall module mark.
Date Set:		04/12/2025
Date & Time Due (the deadline):		19/01/2026 @ 12:00 noon
In accordance with the University Assessment and Feedback Policy, your marked coursework and feedback will be available to you on:			15 working days
You should normally receive feedback on your coursework no later than15 University working days after the formal hand-in date, provided that you have met the submission deadline If for any reason this is not forthcoming by the due date your module leader will let you know why and when it can be expected. The Associate Professor Student Experience (studentexperience-tech@dmu.ac.uk) should be informed of any issues relating to the return of marked coursework and feedback.
When completed you are required to submit your coursework via: 1. A zip file containing your source code submitted to the assessment link 2. A video of no more than 5 minutes, walkthrough of the work done submitted using the assessment link on LearningZone.
Late submission of coursework policy: Late submissions will be processed in accordance with current University regulations. Please check the regulations carefully to determine what late submission period is allowed for your programme.

CSIP5202 Marking Grid:

Criteria	0-49	50-59	60-69	70-100
Design (25%)	Very limited understanding of the problem. No clear requirements, assumptions or constraints identified.	Some understanding of the problem but incomplete justification. A basic high-level design is presented but lacks detail or clarity.	A coherent and logical design is presented, showing understanding of sensors, control and robot behaviour. Chosen solution is appropriate and well- justified.	Comprehensive and well-reasoned design demonstrating deep understanding of the concepts covered.
Implementation (25%)	Minimal or no implementation. Code does not run or does not relate to the design.	Partial implementation, some core components missing or incomplete. Code may run but is unreliable or inconsistent. Limited structure and minimal commenting.	Working implementation that aligns with the design. Code is well structured and reasonably commented. Demonstrates functional robot behaviour (e.g., random wandering, wall following, sensing, control).	Fully functional, efficient and robust implementation. Clean code and meaningful comments. Performance matches or exceeds expected behaviour.
Video walkt hrough (35%)	No submission, video with no audio or video does not demonstrate the system.	Shows the robot but demonstrate limited understanding. Minimal explanation of design or reasoning. Little connection to the marking criteria.	Clear demonstration of the system and its behaviours. Provides a good explanation of design decisions, implementation approach and challenges encountered.	Brilliant walkthrough explaining why decisions were made not just what was done. Connects theory to implementation (e.g., explaining tuning, algorithms, limitation. Includes performance evaluation, test scenarios and reflection on results. Demonstrates depth, clarity and critical thinking.
Additional work (15%)	No additional work beyond basic requirements.	Minor enhancements or explanatory attempts but limited depth.	Meaningful extra work that improves functionality or understanding (e.g., improvedcontroller, additional sensors).	Significant, well-executed extensions that clearly deepen understanding or capability.

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