Computer Science
Grade 5
20 min
5. Robot Control: PID Control and Trajectory Planning
Explore robot control algorithms, including PID control and trajectory planning.
What you'll learn
- Explain the function of each term (Proportional, Integral, Derivative) in a PID controller and how they contribute to achieving a desired setpoint, as demonstrated by correctly answering at least 4 out of 5 multiple-choice questions on a quiz.
- Apply the PID control algorithm to a simulated robotic arm using provided software, tuning the Kp, Ki, and Kd parameters to minimize overshoot and settling time in achieving a target angle, as measured by achieving a settling time within 10% of the target value in at least two out of three trials.
- Design a trajectory for a robot to move between two given points, specifying the position, velocity, and acceleration profiles over time, and justify the chosen trajectory based on factors such as smoothness and minimizing jerk, as evaluated by a rubric assessing the completeness and justification of the designed trajectory.
- Analyze the impact of different trajectory planning algorithms (e.g., linear, polynomial, trapezoidal) on robot performance (e.g., speed, accuracy, smoothness) by comparing the results of simulations using each algorithm on a predefined task, and documenting the findings in a written report.
Tutorial Preview
1
Introduction & Learning Objectives
Learning Objectives
Explain that a robot needs a plan (trajectory) to get from a start to a finish point.
Define 'setpoint' and 'error' in the context of robot movement.
Describe the 'P' (Proportional) part of PID control using a simple analogy.
Describe the 'D' (Derivative) part of PID control using a simple analogy.
Map out a simple grid-based path for a robot that avoids an obstacle.
Calculate the 'error' for a robot trying to follow a line.
Have you ever wondered how a self-driving car stays perfectly in its lane or how a robot arm can grab an object so precisely? 🤖 Let's learn its secrets!
Today, we'll explore two big ideas that make robots smart. First, we'll learn how robots plan their routes, called T...
2
Key Concepts & Vocabulary
TermDefinitionExample
Trajectory PlanningCreating a step-by-step path for a robot to follow, like drawing a route on a map before you start a trip.A robot vacuum cleaner plans a path to cover the whole living room floor without bumping into the sofa.
WaypointA specific spot or point along a robot's planned path. It's like a checkpoint in a video game.To get to the kitchen, a robot's waypoints might be: 1. End of the hallway, 2. Turn right, 3. In front of the fridge.
PID ControlA method a robot uses to continuously check its work and fix mistakes. It helps the robot stay on its planned path, even if it gets bumped.A robot trying to follow a black line uses PID control to quickly turn back towards the line whenever its wheels drift off.
SetpointThe target value or goal the ro...
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Core Syntax & Patterns
The 'P' Rule (Proportional)
Correction = P_Constant * Error
This is the main rule for fixing mistakes. The bigger the error, the bigger the correction. If your robot is far from the line, it makes a big turn. If it's only a little bit off, it makes a small turn.
The 'D' Rule (Derivative)
Correction = D_Constant * (Change in Error)
This rule helps prevent overshooting the target. It looks at how fast the error is changing. If the robot is rushing back to the line very quickly, this rule tells it to slow down its turn so it doesn't fly right past it.
The Trajectory Plan
Path = [Waypoint1, Waypoint2, Waypoint3, ...]
A robot's path is stored as a list of waypoints. The robot's code uses a loop to go through the list, moving from on...
4 more steps in this tutorial
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Challenging
A robot must carry a full cup of water from a table to a person across the room. What are the TWO most important goals for its trajectory planning and PID control?
A.Maximum speed and minimum battery use
B.Smoothness (low acceleration/jerk) and accuracy (reaching the target)
C.Following the shortest possible path and making loud noises
D.Using binary to count steps and having bright lights
Challenging
A robot uses a simple P-controller (`motor_power = Kp * error`) to stay on a line. It works on a flat floor but when it tries to go up a ramp, it always settles slightly off the line. Which PID term should be added to fix this problem?
A.The 'P' term should just be made much larger
B.The 'D' term, to help it predict the ramp
C.The 'I' term, to overcome the constant error caused by gravity
D.None, it's impossible for a robot to go up a ramp on a line
Challenging
A robot needs to visit three waypoints: A, B, and C. Path 1 (A->B->C) is 10 meters long with sharp turns. Path 2 (A->C->B) is 12 meters long but has very gentle curves. If the goal is to finish the task in the SHORTEST TIME, which path is likely the better trajectory?
A.Path 1, because the distance is shorter
B.Both will take the exact same amount of time
C.Neither, the robot should go straight from A to B and skip C
D.Path 2, because the robot can maintain a higher average speed on the gentle curves
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5. Robot Control: PID Control and Trajectory Planning is a Grade 5 Computer Science lesson on ExcelOS.
What will I learn in 5. Robot Control: PID Control and Trajectory Planning?
You'll be able to: Explain the function of each term (Proportional, Integral, Derivative) in a PID controller and how they contribute to achieving a desired setpoint, as demonstrated by correctly answering at least 4 out of 5 multiple-choice….
Is "5. Robot Control: PID Control and Trajectory Planning" free to practice?
Yes. You can read the tutorial preview for free, and signing up for a free ExcelOS account unlocks the full tutorial and all practice questions with instant feedback.
How many practice questions are included with 5. Robot Control: PID Control and Trajectory Planning?
This lesson includes 27 practice questions across multiple difficulty levels, each with instant feedback and explanations.