Lesson Notes By Weeks and Term v4 - SHS 3
Robot Control Principles
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Robot Control Principles
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Subject: Robotics
Class: SHS 3
Term: 2nd Term
Week: 7
Grade code: 3.1.2.LI.3
Strand code: 1
Sub-strand code: 2
Content standard code: 3.1.2.CS.3
Indicator code: 3.1.2.LI.3
Theme: Principles of Robotic Systems
Subtheme: Robot Control Principles
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Welcome, future engineers and innovators! In our last lessons, we learned how to design and build robots to perform specific tasks. But as anyone who has ever built anything knows, things rarely work perfectly on the first try. A robot that is supposed to follow a line might spin in circles. A robotic arm might not grip an object properly. This is normal! The real skill of a robotics expert is not just in building, but in troubleshooting—finding out what's wrong and fixing it. This process of testing, finding flaws, and improving is called iteration.
This lesson focuses on a practical skill: Systematic Troubleshooting and Iterative Design. This is the cycle of building, testing, finding problems, fixing them, and testing again until the robot performs as expected. A. The Core Idea: Iteration
Iteration simply means repeating a process to get closer to a goal. In robotics, it looks like this:
Plan -> Build -> Test -> Analyse -> Refine -> (Repeat) Plan: Design the robot and its code. Build: Assemble the physical robot and upload the code. Test: Run the robot and observe its behaviour. Analyse: Compare what it *actually* does with what it *should* do. Identify the flaws. Refine: Make changes to the hardware or software to fix the flaws. Repeat: Test again to see if your fix worked and didn't create new problems. B. Types of Robot Errors
When a robot fails, the error usually falls into one of these three categories. A good roboticist knows how to check for all three. Mechanical / Design Flaws: These are physical problems with the robot's structure. Definition: Errors related to the body, chassis, wheels, gears, or any moving part. Examples: A wheel is rubbing against the chassis, causing friction and slowing the robot down. The robot is too top-heavy and falls over when it turns. A screw is loose, causing a sensor to be misaligned. A gripper on a robotic arm is not built to hold the shape of the object it needs to pick up (e.g., trying to pick up a ball with flat grippers). Electrical / Hardware Flaws: These are problems with the electronic components and wiring. Definition: Errors related to power, sensors, motors, the microcontroller (e.g., Arduino, Raspberry Pi), or the connections between them. Examples: A wire is connected to the wrong pin on the microcontroller. A motor wire is loose or has a bad connection (a "dry joint" if soldered). The batteries are low, providing insufficient power for the motors to turn properly. A sensor is faulty or damaged. A wire's polarity is reversed (+ and - are swapped), causing a motor to spin backwards. Programming / Algorithmic Flaws: These are errors in the code or the logic behind the code. The robot's "brain" is giving the wrong instructions. Definition: Errors in the software instructions that control the robot's behaviour. Two sub-types: Syntax Errors: Simple typing mistakes that prevent the code from compiling or running (e.g., missing a semicolon `;`, spelling a command wrong). The programming environment usually points these out. Logic Errors (The Tricky Ones): The code runs without any error messages, but the robot does the wrong thing. The instructions are syntactically correct but logically flawed. Examples of Logic Errors: A line-following robot is told `if sensor sees black, turn left`, but the sensor is on the right side of the line. The logic is flawed. An obstacle-avoiding robot is programmed to stop when an object is `< 10 cm` away, but the sensor readings are noisy, so it stops and starts erratically. A delay in the code is too short, causing an action to happen too quickly (e.g., a robotic arm opens its gripper before it has fully lifted an object). C. The Systematic Troubleshooting Process