AI and Robotics Project Development
What this domain tests
AI and Robotics Project Development tests whether you can turn an idea into a testable build: define the problem, set requirements, choose components, integrate, test and document. Expect questions on iteration, evaluation and safe teamwork.
Core rules and concepts
- Start with a problem statement and measurable success criteria, not a component list.
- Requirements should be specific and testable, covering function, performance, cost, power and safety.
- Build a minimum viable prototype, then iterate. Keep a baseline so improvements are measured, not assumed.
- Use flowcharts or pseudocode before coding. Modular code separates sensing, decision and actuation.
- Version control and wiring diagrams make changes traceable. Logs capture failures that a demo hides.
- Test normal, edge and failure cases: missing sensor readings, low battery, blocked actuator and noisy input.
- Document setup, calibration, limitations and test results so another team can reproduce the build.
Worked example
A line-following robot is specified to complete a 3 m track with 90° turns in under 20 s without leaving the line. The team calibrates two reflectance sensors on light and dark surfaces, writes a control loop that steers toward the active sensor, and tests on straight, curved and broken lines. They record completion time and off-line count. If it fails on sharp turns, they lower speed or adjust the turn threshold, then retest against the same baseline.
Traps that cost marks
Do not skip problem definition and jump to hardware. Do not test only the ideal track. Do not leave integration to the last day. Do not claim success without recorded evidence or a baseline.