These Lesson & Labs are coming soon, but for now, students will research and create them
Robo182 Labs - 📖 Lesson Tutorial (Coming Soon)
Robo182 Labs - 📽️ Video / Podcast (Coming Soon)
Robo182 Labs - 📰 Slide Presentation (Coming Soon)
Robotic Lab Ideas - Students can explore these lab ideas and create a step by step guide to accomplish the challenge:
1. Automated Object Picker
Goal: Pick and place objects (e.g., small blocks) between two locations.
Skills Learned: Basic servo control, coordinate mapping.
Steps:
Assemble and calibrate the Robo182 arm.
Write a Python script to control the base and gripper servos.
Define coordinates for the pick-up and drop-off points.
Program the arm to move to the pick-up point and close the gripper.
Move the arm to the drop-off location and open the gripper.
Loop the process for continuous pick-and-place action.
2. Simple Drawing Machine
Goal: Attach a pen to the gripper and draw simple shapes (circle, square).
Skills Learned: Motion planning, coordinate system usage.
Steps:
Attach a pen securely to the gripper.
Calibrate the arm to position the pen tip on a flat surface.
Program basic movement patterns for drawing (e.g., straight lines).
Create coordinate sequences for simple shapes like squares or circles.
Test and adjust pen pressure and path accuracy.
Add functionality for drawing multiple shapes sequentially.
Goal: Use a color sensor to detect objects and sort them into bins.
Skills Learned: Sensor integration, conditional programming.
Steps:
Connect a color sensor to the Raspberry Pi.
Program the sensor to detect and identify colors.
Define sorting bins and corresponding arm positions.
Write code to pick up an object and read its color.
Use conditional statements to determine the drop-off bin based on color.
Test the system with various colored objects.
Goal: Build a Python GUI to control each servo manually through sliders.
Skills Learned: GUI programming, event handling.
Steps:
Install the necessary Python libraries (Tkinter or PyQt).
Create a basic GUI window with slider controls for each servo.
Link the sliders to control the PWM signals for each joint.
Implement “Move” and “Reset” buttons to execute and reset positions.
Add real-time position feedback on the GUI.
Test and refine the interface for smooth operation.
Goal: Integrate a light sensor to make the arm follow a flashlight beam.
Skills Learned: Analog sensor reading, real-time control.
Steps:
Connect a light sensor to the Raspberry Pi.
Write code to read light intensity values.
Define movement logic based on sensor input (e.g., rotate toward the brightest spot).
Attach the sensor to the arm’s base or end-effector.
Program the arm to adjust position dynamically as the light source moves.
Test with different light sources and refine responsiveness.
Goal: Move chess pieces based on predefined commands or input.
Skills Learned: Path planning, fine motor control.
Steps:
Design and label a coordinate grid matching the chessboard.
Write code to map each chess square to robotic arm positions.
Program basic movements (e.g., pick up, move, and place pieces).
Input predefined commands (e.g., “move from A2 to A4”).
Test movements to ensure precision.
Expand the program to handle different piece types and movements.
7. Conveyor Belt Automation
Goal: Simulate an industrial pick-and-place process using a DIY conveyor belt.
Skills Learned: Multi-device synchronization, automation logic.
Steps:
Build a simple conveyor belt using a motor and belt system.
Program the conveyor to run at a consistent speed.
Align the robotic arm with the conveyor belt.
Create a sequence for the arm to pick up objects from the belt.
Synchronize the timing between conveyor movement and arm action.
Add sensors for detecting objects on the belt.
8. Object Detection and Pickup (Basic AI)
Goal: Use a webcam and OpenCV to detect an object and guide the arm to pick it up.
Skills Learned: Computer vision basics, Python libraries integration.
Steps:
Connect a webcam to the Raspberry Pi.
Install OpenCV and configure object detection (e.g., color or shape-based).
Calibrate the camera’s field of view with the arm’s workspace.
Write a script to detect an object and determine its coordinates.
Program the arm to move to the detected position and pick up the object.
Test with different objects and adjust detection accuracy.
Goal: Program the arm to simulate conducting a simple rhythm.
Skills Learned: Timing control, creative sequencing.
Steps:
Define basic conducting gestures (e.g., up-down, left-right).
Program the arm to execute each gesture in sequence.
Synchronize movements with a simple rhythm or metronome.
Add speed adjustments to match different tempos.
Create a loop to repeat the conducting pattern.
Test and refine timing accuracy.
10. Wireless Control with Smartphone
Goal: Build a simple app or browser-based interface to control the arm wirelessly.
Skills Learned: Web development basics, remote communication.
Steps:
Set up a web server on the Raspberry Pi.
Create a simple web interface with buttons for each movement.
Use Flask or another framework to handle web requests.
Link button actions to control the robotic arm’s servos.
Connect the smartphone to the Raspberry Pi's network.
Test the interface and refine for smooth wireless control.
11. Bottle Cap Screwing Mechanism
Goal: Automate the process of screwing bottle caps onto bottles.
Skills Learned: Precision control, rotational alignment, torque calibration.
Steps:
Design a jig to hold bottles securely under the arm.
Program the arm to pick up a cap and position it above a bottle.
Align the gripper rotation with the bottle neck.
Apply rotational movement to screw on the cap.
Calibrate the torque to avoid over-tightening.
Test with different bottle and cap sizes.
12. Letter Sorting Mechanism
Goal: Sort letters or cards based on size or QR code.
Skills Learned: Optical recognition, decision-making logic.
Steps:
Attach a small camera or QR code reader to the arm.
Program the arm to scan and read the code or detect size.
Define sorting bins and corresponding positions.
Create conditional logic to move the letter to the correct bin.
Implement smooth gripping and release mechanisms.
Test the system with various letter sizes and codes.
13. Miniature Assembly Line Simulation
Goal: Simulate a simple multi-step assembly line process.
Skills Learned: Task sequencing, synchronization.
Steps:
Set up workstations representing each assembly step.
Program the arm to perform sequential tasks at each station.
Synchronize timing for each step.
Test with small parts (e.g., building a model from blocks).
Implement error detection (e.g., missing parts).
Expand to handle more complex tasks in sequence.
14. Maze Navigation Challenge
Goal: Move an object through a pre-designed maze.
Skills Learned: Path planning, obstacle avoidance.
Steps:
Design a physical maze with walls.
Program the arm to map out and follow a path through the maze.
Implement movement commands to navigate tight spaces.
Add sensors to detect obstacles.
Test and refine path accuracy.
Create challenges with different maze layouts.
15. Robotic Arm Game (Catch the Ball)
Goal: Develop a game where the arm attempts to catch a rolling ball.
Skills Learned: Real-time motion, sensor feedback integration.
Steps:
Set up a track or surface where the ball can roll.
Attach a sensor to detect the ball's position.
Program the arm to predict and move to the ball’s position.
Calibrate the gripper to close at the right moment.
Test and adjust for ball speed and arm response.
Add a scoring system for catching success.
Goal: Program the arm to set up a domino chain automatically.
Skills Learned: Precise placement, sequence control.
Steps:
Program the arm to pick up and place dominoes vertically.
Define positions for each domino in the sequence.
Implement logic to maintain consistent spacing.
Calibrate movements for accuracy.
Test by knocking down the domino chain.
Add functionality to adjust patterns or curves.
17. Simple Object Weighing System
Goal: Weigh objects using a load sensor and sort them by weight.
Skills Learned: Sensor calibration, data processing.
Steps:
Connect a load cell sensor to the Raspberry Pi.
Calibrate the sensor to detect object weight accurately.
Program the arm to place objects on the sensor.
Read the weight and categorize objects into bins.
Implement logic to handle weight ranges.
Test with various objects of different weights.
Goal: Solve a simple jigsaw puzzle using vision and manipulation.
Skills Learned: Image recognition, multi-step task planning.
Steps:
Attach a camera for puzzle piece detection.
Program image recognition to identify piece shapes.
Define positions for each piece on the puzzle board.
Guide the arm to pick and place each piece correctly.
Implement logic to handle different puzzle layouts.
Test and refine accuracy for piece fitting.
19. Cup Stacking Challenge
Goal: Program the arm to stack cups into a pyramid structure.
Skills Learned: Stability control, repetitive motion sequencing.
Steps:
Calibrate the arm to pick up plastic cups.
Program movements to stack cups in a row.
Define the sequence for stacking layers into a pyramid.
Implement checks to ensure stability.
Test for accuracy and adjust cup positioning.
Add a timer to create a challenge.
20. Robotic Arm Typing Simulation
Goal: Program the arm to type simple words on a keyboard.
Skills Learned: Precision targeting, sequence automation.
Steps:
Set up a keyboard within the arm’s reach.
Map key positions to the robotic arm’s workspace.
Program movements to press individual keys.
Define sequences to type simple words (e.g., “hello”).
Test accuracy and refine for different key sizes.
Add functionality to type more complex phrases.
