TECHNOLOGY-11 · Advanced · ENGLISH · PLANNED
Follow a real task through a system, then design and troubleshoot it.
Study time is an initial activity estimate, excluding extra reading, revision and extended laboratory or project work. Videos and question bodies have not been produced by adding this outline.
Complete these courses or demonstrate equivalent knowledge. These are recommended prerequisites, not enforced enrolment locks.
YouTube playlist: ARK Technology | Robotics, Control and Automation
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Sign in to save this learning pathPractical outcome: Model the workspace of a simple two-link arm.
Explain coordinate frames using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain rotation matrices using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain homogeneous transforms using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain forward kinematics using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Use the first concepts from this section. Model the workspace of a simple two-link arm. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain inverse kinematics using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain jacobians using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain workspace limits using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Explain singular configurations using a visual and one worked real-world example. Context: Model the workspace of a simple two-link arm. End with a prediction or check-for-understanding.
Model the workspace of a simple two-link arm. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Coordinate frames, Rotation matrices, Homogeneous transforms and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Tune a simulated temperature controller and report overshoot.
Explain open-loop control using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain feedback using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain transfer functions using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain stability using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Use the first concepts from this section. Tune a simulated temperature controller and report overshoot. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain proportional control using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain integral control using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain derivative control using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Explain pid tuning using a visual and one worked real-world example. Context: Tune a simulated temperature controller and report overshoot. End with a prediction or check-for-understanding.
Tune a simulated temperature controller and report overshoot. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Open-loop control, Feedback, Transfer functions and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Plan a collision-free route on a toy grid.
Explain sensors and actuators using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain state estimation using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain kalman filter concept using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain localisation using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Use the first concepts from this section. Plan a collision-free route on a toy grid. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain mapping using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain motion planning using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain human override using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Explain validation scenarios using a visual and one worked real-world example. Context: Plan a collision-free route on a toy grid. End with a prediction or check-for-understanding.
Plan a collision-free route on a toy grid. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Sensors and actuators, State estimation, Kalman filter concept and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Combine all three sections: Plan a collision-free route on a toy grid. Submit an original worked artifact, evidence or tests, assumptions and a reflection. Rubric: correctness, method, practical usefulness, reproducibility and communication. Self-reviewed, not certified.
6–12 balanced questions sampling every section of Robotics, Control and Automation, including interpretation, calculation or reasoning, a misconception and a new application. Passing is 70%; review errors before retrying.
System diagrams, design reviews and bounded prototypes. Guided work leads to an independent attempt, with a diagram, explanation, trace, calculation or tested artifact. Question bodies are generated when opened in your private learning path. Programming submissions are stored as text; the platform does not execute submitted code.
Use original or appropriately licensed datasets. Practical science activities use models or supplied data unless a qualified supervisor has reviewed a physical experiment.
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