The project is a term-long activity in which students develop, test, and progressively integrate a MATLAB/Simulink simulator for an autonomous aircraft together with its estimation, control, guidance, and navigation functions. The project consists of twelve staged deliverables that culminate in an integrated simulator and a final presentation and project demonstration. Each deliverable extends the work completed in earlier stages, so groups are expected to maintain previously developed capabilities and incorporate feedback as the project progresses.
Group Formation and Responsibilities
Students will complete the project in groups of two or three. The instructor will determine and announce the required group size at the start of the term based on class enrollment. Students are responsible for forming a group and self-enrolling in a project group on Brightspace by the deadline announced during the first week of classes. Students who have not joined a group by the deadline will be assigned to one by the instructor. Any exception to the announced group size or change in group membership requires prior approval from the instructor. Concerns about participation or group functioning should be raised as early as possible so that appropriate arrangements can be considered.
All group members are expected to participate actively throughout the term and to share responsibility for planning, implementation, testing, interpretation of results, and preparation of submissions. Each member should understand the complete project and be prepared to explain the group's models, design decisions, results, and conclusions. Each deliverable normally receives a common group grade, although individual grades may be adjusted when there is clear evidence of a substantial difference in contribution.
Weekly Meetings with the TA
Each project group will meet with the TA once a week for 30 minutes throughout the term. Meetings will be held in person unless alternative arrangements are made with the TA.
During each meeting, students will briefly discuss their progress on the current deliverable and raise questions or difficulties encountered in their work. The TA will answer questions, clarify deliverable requirements, and provide guidance and technical support. All group members should be prepared to participate in the discussion and explain their group's progress.
The meetings are intended to support project development and are not a form of assessment. Attendance is nevertheless mandatory for all group members. A student who is unable to attend a meeting must notify the TA in advance and provide an explanation for the absence. Any necessary alternative arrangements should be discussed with the TA and course instructor.
Deliverables and Submission
One submission per group is required for each deliverable. Submissions will normally include the required MATLAB/Simulink models and supporting files, relevant test cases, results presented through appropriate plots, tables, or visualizations, and a brief discussion of the findings. Information about file formats, deadlines, and deliverable requirements will be posted on Brightspace.
The final project presentation is the last deliverable. Each group will present the integrated system, describing its architecture, major design decisions, verification approach, performance, and limitations, and will demonstrate its operation. All group members are expected to participate in the presentation and demonstration and to be prepared to discuss the complete system.
Each deliverable must also include a brief author statement identifying the contributions of every group member. All group members are expected to participate actively throughout the term and contribute equitably to the work submitted. Any substantial differences in contribution must be explained in the author statement and may result in individual project grades being adjusted on a case-by-case basis.
The project deliverables and due dates shown in the table below are tentative and may be adjusted during the term.
| Project Deliverable | Due Date | Weight |
|---|
| Aircraft visualization: Three-dimensional aircraft visualization, coordinate-transformation tests, and a short demonstration. | Sep 21 | 2% |
| Rigid-body dynamics: 6-DOF aircraft model, force- and moment-axis tests, and evidence of coupled rotational motion. | Sep 28 | 3% |
| Flight simulation: Gravitational, aerodynamic, propulsive, and wind models integrated into the nonlinear aircraft simulation, with evidence of the resulting control response. | Oct 5 | 4% |
| Linear design models: Trim conditions, transfer-function and state-space models, modal calculations, and comparisons with the nonlinear simulation. | Oct 15 | 5% |
| Autopilot: Longitudinal and lateral control loops, controller-design rationale, and evaluation of commanded responses and actuator limits. | Oct 26 | 7% |
| Sensors: Development and validation of gyro, accelerometer, pressure, and GPS sensor models, including output sign and magnitude, noise characteristics, and sampling rates. | Nov 2 | 3% |
| State estimation: Implementation and evaluation of state-estimation methods, comparisons between estimated and simulated aircraft states, and closed-loop operation using estimated states. | Nov 12 | 7% |
| Guidance models: Development and validation of reduced-order closed-loop models for guidance design through parameter identification and comparison with the nonlinear aircraft simulator. | Nov 16 | 4% |
| Path following: Straight-line and orbit-following results under calm and windy conditions, with quantitative measures of tracking performance. | Nov 23 | 4% |
| Path management: Waypoint, fillet, and Dubins-path transition logic demonstrated in the integrated simulation. | Nov 30 | 5% |
| Path planning: Point-to-point and coverage planning using rapidly exploring random trees (RRTs) and Dubins paths, with smoothing and validation on reduced-order and 6-DOF models. | Dec 7 | 6% |
| Final project presentation: Presentation and demonstration of the integrated autonomous-aircraft simulator, including its architecture, major design decisions, verification results, performance, and limitations. | Dec 14 | 10% |
GenAI Use in the Project
For deliverables 1–11, GenAI may be used under Level B (AI-assisted idea generation and structuring) as a learning and debugging aid. Students may ask conceptual questions, seek explanations of MATLAB or Simulink functionality and errors, and explore diagnostic strategies. This use should be comparable to consulting MATLAB documentation or seeking general troubleshooting guidance. GenAI must not be used to solve a deliverable, develop a required algorithm, or generate code, models, analyses, results, figures, or interpretations for submission.
Students must design and implement all submitted MATLAB code and Simulink models and independently verify and test any guidance received from GenAI. Every group member must be prepared to explain and justify the submitted work. Because autopilot and flight-control software is commonly safety- and mission-critical, submitted code must be correct, robust, computationally efficient, free of known defects, and thoroughly tested. Unverified or insufficiently understood work does not meet the standards of this course. GenAI output is not a substitute for engineering judgement or verification.
For the same deliverables 1–11, GenAI may be used under Level C (AI-assisted editing) to polish the grammar, clarity, and style of prose written by students. It may not add or change technical claims, reasoning, findings, or interpretations. Students must understand and be prepared to explain all submitted written text.
For deliverable 12, the final project presentation, Level A applies to the technical content and delivery. Students must develop and explain the methods, results, analyses, conclusions, and limitations without GenAI assistance, and GenAI may not prepare technical speaking notes or assist during the presentation or question period.
GenAI may be used to support the visual preparation of the final presentation. Under Level C, it may polish slide text originally written by the students without adding or changing technical content. Under Level D, it may help organize a summary slide from points already written by the students or create illustrative diagrams based on student-provided specifications. Students must review all AI-assisted materials for accuracy, understand and be able to explain them, and cite any AI-generated or AI-modified content.
See the Generative Artificial Intelligence section for the complete requirements.