1. Project Overview
This project focuses on designing and building an intelligent car with autonomous obstacle avoidance capabilities. Students will comprehensively utilize Mind+ graphical programming, the Arduino hardware platform, and various sensor/actuator modules to achieve functions such as mechanical structure assembly, ultrasonic distance measurement, and servo steering control through phased tasks. The project deeply integrates the Doubao Classroom Assistant AI, providing students with real-time learning support and personalized guidance, fostering interdisciplinary engineering practice skills and innovative thinking.
2. Overall Project Goals
1. Knowledge and Skills Goals
◦ Master the principles of distance measurement and signal processing methods of ultrasonic sensors
◦ Understand the differential control technology of the L9110 motor driver module
◦ Learn servo angle control and PWM signal output
◦ Achieve modular programming and multi-task collaborative control
2. Process and Method Goals
◦ Cultivate systematic thinking through the engineering process of “mechanical design – circuit connection – software debugging”
◦ Learn to use the serial monitor and AI-assisted fault diagnosis
3. Emotional Attitude and Values Goals
◦ Appreciate the application value of intelligent control technology in smart homes and industrial control
◦ Cultivate a rigorous engineering attitude and environmental awareness (using waste cardboard)
3. Required Hardware
1. Arduino Nano + Expansion Board
2. Ultrasonic Sensor
3. 9g Servo (with angle code)
4. L9110 Motor Driver Module
5. TT DC Motor (with tires)
6. Universal Wheel (front wheel)
7. Corrugated cardboard and auxiliary materials (wood sticks, zip ties, etc.)
8. Battery Holder (4 AA batteries)
9. Dupont Wires, Hot Glue Gun, and other tools
4. Class Schedule and Lesson Design
First Lesson: Building the Car’s Mechanical Structure
1. Learning Objectives
◦ Master the lightweight design and load-bearing structure of the cardboard car body
◦ Achieve stable installation of the motor and wheels
2. Key Teaching Points
◦ Focus: Car body frame design and wheelbase determination
◦ Difficulty: Coaxial calibration of the motor shaft and tire
3. Teaching Steps
◦ Introduction (5 minutes): Show a video of industrial AGV handling robots to introduce the functional requirements of the obstacle-avoiding car
◦ Design Practice (30 minutes):
◦ Create the car body frame using corrugated cardboard
◦ Install the motor bracket and wheels (rear-wheel drive, front universal wheel)
◦ Structure Optimization (15 minutes):
◦ Add servo bracket and sensor fixed position
◦ Test the balance of the car body
◦ AI Interaction: Doubao provides 3D printing alternatives and reminds safety precautions for material cutting
Second Lesson: Ultrasonic Sensor Debugging
1. Learning Objectives
◦ Master the principles of distance measurement and signal acquisition of ultrasonic sensors
◦ Display distance values on the OLED screen
2. Key Teaching Points
◦ Focus: Timing control of Trig/Echo pins
◦ Difficulty: Measurement accuracy optimization
3. Teaching Steps
◦ Review Introduction (5 minutes): Review the car body structure and introduce the need for obstacle detection
◦ Knowledge Explanation (15 minutes):
◦ Working principle of ultrasonic sensors
◦ Use of distance measurement blocks in Mind+
◦ Hardware Practice (20 minutes):
◦ Connect the sensor to D2/D3 pins
◦ Write code: Measure distance and display on serial monitor (unit: cm)
◦ Calibration Experiment (10 minutes):
◦ Test measurement errors at different distances
◦ AI Interaction: Doubao provides calibration parameter suggestions and real-time signal quality monitoring
Third Lesson: Servo Steering System
1. Learning Objectives
◦ Master servo angle control and timing coordination
◦ Achieve linkage between steering actions and distance measurement
2. Key Teaching Points
◦ Focus: Servo initialization and angle adjustment
◦ Difficulty: Coordination of steering actions and obstacle avoidance strategies
3. Teaching Steps
◦ Task Introduction (5 minutes): Show a diagram of the servo steering structure and clarify action requirements
◦ Knowledge Explanation (15 minutes):
◦ Working principle of servos and control signals (50Hz PWM)
◦ Use of the servo library in Mind+
◦ Hardware Practice (20 minutes):
◦ Connect the servo to D9 pin
◦ Write code: Turn the servo 90° when an obstacle is detected
◦ Mechanical Integration (10 minutes):
◦ Create a steering linkage structure using wood sticks
◦ Adjust servo torque and rotation speed
◦ AI Interaction: Doubao provides angle calibration guidelines and demonstrates mechanical structure optimization
Fourth Lesson: Obstacle Avoidance Function Programming
1. Learning Objectives
◦ Master the programming logic for collaborative work of multiple modules
◦ Achieve dynamic obstacle avoidance path planning
2. Key Teaching Points
◦ Focus: Logical integration of ultrasonic distance measurement and motor control
◦ Difficulty: Implementation of non-blocking delays and path optimization
3. Teaching Steps
◦ Task Introduction (5 minutes): Clarify complete functional requirements (detection → judgment → steering → recovery)
◦ Programming Practice (30 minutes):
◦ Write code: Trigger steering when distance < 20cm
◦ Add steering priority (left/right/back)
◦ Joint Debugging Optimization (15 minutes):
◦ Test response speed to different obstacles
◦ Adjust steering angle and delay time
◦ Fault Diagnosis (10 minutes):
◦ Address common issues (false positives, spinning in place)
◦ Learn to use serial logs for debugging assistance
◦ AI Interaction: Doubao provides obstacle avoidance algorithm suggestions and analyzes loss of control reasons
Fifth Lesson: System Integration and Function Expansion
1. Learning Objectives
◦ Achieve programming logic for collaborative work of multiple modules
◦ Enhance the innovation and practicality of engineering design
2. Key Teaching Points
◦ Focus: Multi-task processing and resource management
◦ Difficulty: Code optimization for complex functions
3. Teaching Steps
◦ Task Introduction (5 minutes): Clarify complete functional requirements (manual/automatic mode switching)
◦ Programming Practice (30 minutes):
◦ Integrate distance measurement, steering, and motor control code
◦ Joint Debugging Optimization (15 minutes):
◦ Test responses under different lighting conditions
◦ Adjust parameters for smooth transitions
◦ Fault Diagnosis (10 minutes):
◦ Address common issues (remote control delay, motor noise)
◦ Learn to use serial logs for debugging assistance
◦ AI Interaction: Doubao provides code optimization plans and generates performance analysis reports
5. Assessment Methods
1. Process Evaluation (40%)
◦ Stability of mechanical structure (10%)
◦ Standardization of circuit connections (10%)
◦ Reasonableness of code logic (10%)
◦ Problem-solving ability (10%)
2. Summative Evaluation (60%)
◦ Completeness of obstacle avoidance function (30%)
◦ Innovation of structural design (20%)
◦ Presentation of work (10%)
6. Safety Tips
1. Ensure correct connection of positive and negative terminals of the battery holder to avoid short circuits
2. Ensure wheels are free of obstruction when the motor is running
3. Exercise caution with high-temperature protection when using a hot glue gun
7. Doubao AI Application Design
1. Real-time Guidance: Provide step-by-step voice prompts during hardware connections, code writing, and other stages
2. Error Diagnosis: Automatically identify circuit errors and code logic errors and provide modification suggestions
3. Resource Expansion: Push materials on path planning algorithms and industrial robot cases
4. Learning Archives: Record student debugging data and generate personalized ability analysis reports
8. Teaching Resources
1. Mind+ software and extension libraries
2. Technical documentation for each module
3. Engineering log templates
4. Ultrasonic sensor temperature compensation reference table