Project: Gismo - Multi-Sensor Robot
Gismo is a feature-packed robot built on a Raspberry Pi. It combines a variety of sensors, motors, and interactive components to create a responsive and engaging robotic experience.
Building G.I.S.M.O has been an incredible experience, one that reflects my approach to problem-solving: dive in, experiment, adapt, and refine. It’s messy, exciting, and immensely rewarding—a true labor of love.
Key Features & Capabilities
- Motor Control: Gismo can move forward, backward, and turn using two DC motors.
- Neck Servo: A servo motor allows Gismo to turn its "head" and scan its surroundings.
- Obstacle Avoidance: Gismo uses an ultrasonic sensor to detect objects in its path and avoid collisions.
- Edge Detection: Edge sensors prevent Gismo from falling off surfaces.
- Buzzer Feedback: A buzzer plays melodies to indicate different events, such as object detection or edge detection.
- RGB LED Feedback: An RGB LED provides visual cues, changing color based on Gismo's actions.
- Touch Sensor Interaction: Gismo reacts to touch with a shaking motion.
- IR Distance Sensor: An infrared distance sensor helps Gismo avoid obstacles while reversing. (Note: This might be the HCSR04 or another specific IR sensor, clarify if needed)
- Button Control: A button triggers debugging actions and sensor tests.
- Camera Functionality: Gismo can take pictures when it detects an object using its Pi Camera.
- IR Remote Control: Control Gismo's movements with an infrared remote.
- Sound Sensor: Gismo can react to sounds in its environment.
- OLED Display: A small OLED screen (SSD1306) displays a "face" that changes expression based on Gismo's status (happy or sad).
- IMU (Inertial Measurement Unit): An MPU9250 IMU provides acceleration, gyroscope, and magnetometer data for advanced navigation and orientation sensing.
- Primary Language: Python
- Key Libraries:
- RPi.GPIO
- PIL (Pillow)
- adafruit_ssd1306
- adafruit_pca9685
- evdev
- mpu9250_jmdev
- libcamera-still (for camera functionality via subprocess)
- [Any custom libraries/modules you wrote]
- Functionality: Motor control, sensor data acquisition, basic navigation algorithms (e.g., obstacle avoidance, dead reckoning for path estimation).
- [Add more details about your software architecture, specific algorithms (like how dead reckoning is implemented or used), or interesting coding challenges]
- Component Integration: Ensuring all sensors (ultrasonic, IR, IMU, edge sensors, touch, sound) communicated reliably with the Pi, often requiring careful library selection and debugging of I2C and GPIO interactions.
- Power Management: Balancing the power requirements of the motors, servos, Pi, and various sensors from a single LiPo battery, and mitigating potential electrical noise from the motors affecting sensor readings.
- Sensor Calibration & Interference: Fine-tuning the sensitivity of sensors like the ultrasonic and sound sensor, and addressing potential interference between them. Calibrating the MPU9250 IMU was also a detailed process.
- Movement Mechanics: Achieving smooth and predictable movement with the DC motors and L298N driver, including refining PWM values for speed control and turning.
- Software Debugging: Iteratively developing and debugging the Python code for sensor polling, motor control logic, obstacle avoidance algorithms, and the state machine for Gismo's "face" expressions.
- Integration of advanced sensors (e.g., LIDAR or Time-of-Flight).
- Machine learning for object recognition and more sophisticated decision-making.
- Enhanced navigation algorithms for complex environments, potentially incorporating SLAM (Simultaneous Localization and Mapping) capabilities.
- Implementation of voice command recognition for more natural interaction.
- Development of a web interface for remote monitoring and control.
- Improved power efficiency and battery management for longer operational times.
- Clone the repository:
git clone https://github.com/JamesTheGiblet/Project-G.I.S.M.O.git(Replace with your actual username if different) - Install the required libraries:
pip install -r requirements.txt(Ensure `requirements.txt` is in the repo) - Connect the hardware components according to the wiring diagram/table.
- Configure the IR receiver: Find the correct
eventXpath for your IR receiver usingls /dev/input/and update the `device_path` variable in the code. - Run the code:
python gismo_v1.13.py(Or your main script name) - Use the IR remote to control Gismo's movements.
- Press the button to run sensor tests.
- Gismo will automatically avoid obstacles and edges.
- Observe the RGB LED and OLED display for visual feedback.
- Listen to the buzzer for audio cues.
Technical Architecture
The robot’s design integrates key hardware components like the Raspberry Pi, sensors, motor controllers, and a power management unit. The software uses a layered architecture for easier debugging and future enhancements.
Hardware Components & GPIO Assignments
| Component | Wire/Signal | Colour | Connection/Pin | Power Source |
|---|---|---|---|---|
| Raspberry Pi Zero 2W | power | red/black | PCA9685 0 | PCA2 |
| SSD1306 Display | SDA | White | PCA9685 SDA | PCA out |
| SCL | Blue | PCA9685 SCL | PCA out | |
| PCA9685 PWM Driver | SDA | Yellow | Pi GPIO 2 | battery |
| SCL | Blue | Pi GPIO 3 | battery | |
| MPU9250 IMU | SDA | White | PCA9685 SDA | PCA15 |
| SCL | Blue | PCA9685 SCL | - | |
| Pi Camera Rev 1.3 | - | - | CSI port | - |
| 9G Servo (left) | - | - | PCA9685 Channel 0 | PCA0 |
| 9G Servo (right) | - | - | PCA9685 Channel 1 | PCA1 |
| 9G Servo (head) | - | - | PCA9685 Channel 14 | PCA14 |
| KY-016 RGB LED (Red) | Red | Red | PCA9685 Channel 13 | PCA13 |
| KY-016 RGB LED (Green) | Green | Green | PCA9685 Channel 12 | - |
| KY-016 RGB LED (Blue) | Blue | Blue | PCA9685 Channel 11 | PCA10 |
| L298N Motor Driver (power) | - | - | - | PCA11 |
| L298N Motor Driver Int1 | Int1 | Blue | PCA9685 Channel 7 | PCA11 |
| L298N Motor Driver Int2 | Int2 | Green | PCA9685 Channel 8 | PCA9 |
| L298N Motor Driver Int3 | Int3 | White | PCA9685 Channel 10 | PCA8 |
| L298N Motor Driver Int4 | Int4 | Yellow | PCA9685 Channel 9 | PCA7 |
| KY-033 Edge Sensor (right) | Signal | Green | Pi GPIO 12 | PCA5 |
| KY-033 Edge Sensor (left) | Signal | Green | Pi GPIO 13 | PCA4 |
| CHQ1838 IR Receiver | Signal | Green | Pi GPIO 16 | PCA12 |
| TTP223B Touch Sensor | Signal | Green | Pi GPIO 17 | PCA8 |
| KY-006 Passive Buzzer | Signal | White | Pi GPIO 18 | PCA6 |
| TS-YM-115 Sound Sensor | Signal | White | Pi GPIO 21 | PCA9 |
| HCSR04 Ultrasonic Echo | Echo | Green | Pi GPIO 22 | PCA7 |
| HCSR04 Ultrasonic Trigger | Trigger | Blue | Pi GPIO 23 | - |
| TP-4056 USB Charger | - | - | LiPo 3.7V | PCA3 |
| Switch 999330 | - | - | LiPo 3.7V | - |
| LiPo 3.7V 1100mAh 903042 | - | - | TP-4056 USB Charger | - |
This table summarizes the main components, their wiring, GPIO assignments, and power sources for Gismo.
Software & Programming
Build Process & Challenges
The construction of Gismo was an iterative journey, starting with a custom 3D-printed chassis designed to house all components compactly and allow for easy access. This was followed by gradually integrating each sensor and actuator. Wiring was a significant challenge, meticulously routing connections for the numerous components to the Raspberry Pi and PCA9685 servo driver while keeping the build clean and manageable.
Key challenges encountered included:
This project was a profound learning experience, reinforcing the importance of modular design for easier debugging, systematic troubleshooting, and the practical application of electronics and programming skills in a complex, integrated system. The "dive in and figure it out" approach was essential, leading to many "aha!" moments and a much deeper understanding of robotics.
Future Enhancements
Setup & Usage
Usage Instructions:
View G.I.S.M.O Project on GitHub
