Lesson Notes By Weeks and Term v4 - SHS 2
Robot Control Principles
Download the Lessonotes Mobile Ghana app for faster lesson access on Android and iPhone.
Robot Control Principles
Download the Lessonotes Mobile Ghana app for faster lesson access on Android and iPhone.
Subject: Robotics
Class: SHS 2
Term: 1st Term
Week: 14
Grade code: 2.1.2.LI.2
Strand code: 1
Sub-strand code: 2
Content standard code: 2.1.2.CS.2
Indicator code: 2.1.2.LI.2
Theme: Principles of Robotic Systems
Subtheme: Robot Control Principles
This page supports the lesson note with a companion video and a short classroom-ready summary.
For class groups and homework, share this lesson page so learners also get the summary, objectives, and full lesson context.
Welcome, future engineers and innovators! Today, we are going to learn one of the most fundamental concepts in making robots "smart": the Finite-State Machine (FSM). Think about a simple traffic light at a junction in Accra or Kumasi. It doesn't think for itself, but it follows a strict set of rules: it stays GREEN for a while, then changes to YELLOW, then to RED, and then back to GREEN. It operates in a predictable, step-by-step manner. This simple logic is the heart of an FSM.
What is a Finite-State Machine (FSM)?
A Finite-State Machine is a model of computation used to design computer programs and digital logic circuits. In simple terms, it's a way of describing a system that can only be in one of a limited ("finite") number of conditions or "states" at any given time.
Imagine a simple fan switch in your classroom. It has a limited number of states: `OFF`, `SPEED 1`, `SPEED 2`, `SPEED 3`. You can't be in `SPEED 1` and `SPEED 2` at the same time. You move from one state to another by providing an input (turning the knob). That's an FSM! The Four Key Components of an FSM
To build an FSM, we need to understand its four essential parts. Let's use the example of an automatic door at a bank or supermarket. States: A state is a specific condition or mode of the system. A state describes what the robot is currently *doing* or *being*. *Example:* The automatic door has two primary states: `DOOR_CLOSED` and `DOOR_OPEN`. Inputs (or Conditions/Events): An input is an event or a sensor reading from the environment that triggers a change from one state to another. *Example:* The input for the automatic door is the motion sensor. We can call this input `Person_Detected` or `Person_Not_Detected`. Transitions: A transition is the actual move from one state to another. A transition only happens when a specific input (condition) is met. *Example:* When the door is in the `DOOR_CLOSED` state and the input `Person_Detected` becomes true, it *transitions* to the `DOOR_OPEN` state. Outputs (or Actions): An output is what the system *does* while it is in a particular state or during a transition. These are the commands sent to the robot's actuators (motors, lights, etc.). *Example:* In the `DOOR_OPEN` state, the output action is "Activate motor to keep door open". In the `DOOR_CLOSED` state, the output action is "Ensure motor is off and door is shut". Modelling an FSM: The Two Main Tools