ST2: Lesson 1: Obstacle-Avoiding Drone Systems

Can a drone really think fast enough to avoid disaster?

In this KS3 / lower secondary computing lesson, students take on the role of drone navigation designers. They explore how sensor data triggers logic gate outputs, how the ALU processes this to make a movement decision, and how the system avoids collisions in real-world environments. Learners engage with decision tables, binary inputs, and gate diagrams to simulate how a drone uses logic to fly safely.

This lesson builds on ST1_1 by applying those same input and output concepts to a mobile system, introducing autonomous logic, binary triggers, and ALU-controlled decisions.

Through this, students uncover:

• How input devices provide real-time binary signals to the processor
• What the ALU does in this system to make logical decisions
• How logic gates (AND, OR, NOT) support movement outcomes
• The concept of a truth table as a model for decision-making
• Why binary logic and performance-based safety matters in this scenario

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