Session Length: 50-60 minutes
Learning Style: Experimental learning, creative problem-solving
Key Learnings (Sessions 1-10):
- Session 1-2: Refresher on Arduino syntax; understanding response times of sensors/actuators.
- Session 3-4: Introduction to advanced logic (e.g., combining sensor data for decision-making).
- Session 5-6: Design challenges focused on obstacle detection, avoidance, and mapping environments.
- Session 7-8: Introduction to creating custom arenas and real-world simulations using craft materials.
- Session 9-10: Final project: designing an interactive, autonomous bot for complex tasks (e.g., object sorting, mapping obstacles).
Equipment Needed: (Included in the kit) M3D Go, Arduino IDE, sensors, servo motors, actuators, crafting materials, Not included in the kit: glue gun for arena creation, laptop
Course Breakdown
1. Bot Basics: Movement and Code
Students will begin by writing simple code to control the bot’s movement (forward, backward, rotate) using the Arduino platform. They’ll manually operate the bot to understand how each line of code translates to physical actions, fostering a strong intuition about coding and movement.
2. Sensing the World: Feedback in Action
In this lesson, students will explore how sensors gather data. They will write code to display sensor readings on the bot’s screen and conduct experiments to see how different surfaces affect sensor performance. This hands-on activity will help them grasp the concept of response times and how sensors interact with the environment.
3. Mapping Obstacles: The Scan and Avoid
Students will use the distance sensor to program the bot to scan its environment for obstacles. They will learn to implement simple avoidance strategies based on sensor data, allowing the bot to navigate around obstacles effectively.
4. Enhancing Line Following: Dynamic Adjustments
Building on previous line-following lessons, students will refine their algorithms to adjust for different brightness levels and line widths. They’ll test their bots on various track designs to see how well they adapt to changes in the environment.
5. Automated Sorting Challenge – Sensitive or Not?
Students will use glue guns and other materials to design grocery robot for their robots. Students will build and code a robot to sort items by sensitivity and weight using motorized attachments and Web BLE inputs. They’ll learn adaptive sorting logic, practicing coding and teamwork as they create an automated system inspired by real-world warehousing. By exploring how conditions like weight and fragility affect sorting, students will see the practical applications of robotics in logistics and inventory management.
6. Programming with Loops – Interactive Calculator with Robotics
In this session, students will learn to use for loops to create an interactive calculator with their robot. By coding prompts and utilizing Web BLE, they’ll build a program that takes user input to perform calculations and uses the robot’s display for feedback, including fun emojis. Students will also code the robot to move a distance based on the calculation’s result, reinforcing the concepts of repetition, conditional prompts, and practical applications of loops in programming.
7. Follow the Leader – Reactive Robotics
In this session, students program robots to follow a “leader” based on real-time distance readings, exploring sensor response times and the impact of delay in robotics. Through conditional coding, they’ll control their robot’s movements and emoji expressions based on proximity, and experiment with adaptive roles, allowing any robot to become the leader. This hands-on activity highlights flexibility and responsiveness in automated systems.
8. Advanced Motor Control and Sensor-Based Data Analysis
In this session, students will learn to smooth robot movements using acceleration and explore real-time mapping through distance plotting. They’ll experiment with motor control, line sensing for color detection, and Web BLE plotting to visualize data, building a deeper understanding of robotics applications in environmental awareness and navigation.
9. Final Project: The Arena Challenge
Students will put all their learning together in a final project where their bots must navigate the arena they created, completing tasks like avoiding obstacles, following paths, and detecting treasures. They’ll present their designs and code, explaining their logic and the challenges they faced.
10. Showcase and Reflection: What We’ve Learned
In the final session, students will showcase their bots in a friendly competition, demonstrating their functionality in the arena. They will reflect on their learning journey, discussing the relationships between code, design, and robotic behavior.