https://github.com/joshuaj03/swheels
SWheels - Smart Autonomous Voice-Controlled Wheelchair
https://github.com/joshuaj03/swheels
assistive-technology autonomous-wheelchair computer-vision disability-assistance disability-tech healthcare-innovation machine-learning main-project raspberry-pi robotics smart-wheelchair voice-controlled-wheelchair yolo11
Last synced: 7 months ago
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SWheels - Smart Autonomous Voice-Controlled Wheelchair
- Host: GitHub
- URL: https://github.com/joshuaj03/swheels
- Owner: joshuaj03
- License: apache-2.0
- Created: 2025-03-13T18:22:25.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-03-15T05:47:58.000Z (7 months ago)
- Last Synced: 2025-03-23T04:17:50.797Z (7 months ago)
- Topics: assistive-technology, autonomous-wheelchair, computer-vision, disability-assistance, disability-tech, healthcare-innovation, machine-learning, main-project, raspberry-pi, robotics, smart-wheelchair, voice-controlled-wheelchair, yolo11
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SWheels - Smart Autonomous Voice-Controlled Wheelchair
## Overview
SWheels is an intelligent, voice-controlled wheelchair designed for individuals with partial or complete paralysis. Our primary goal is to implement a robust autopilot mode, allowing the wheelchair to navigate independently from point A to point B. Additionally, SWheels supports multiple control mechanisms, including voice commands and a joystick, ensuring ease of use. It also features automatic speed adjustment for inclines and real-time obstacle detection for enhanced safety.
## Features
### Phase 1 (Current Implementation)
- **Voice and Joystick Control**: Users can operate the wheelchair using voice commands or a joystick.
- **Automatic Speed Adjustment**: The wheelchair adjusts its speed dynamically when going uphill or downhill for safety and comfort.
- **Incline Lock Mechanism**: Ensures stability on slopes.
- **Obstacle Detection and Avoidance**: Uses ultrasonic sensors for real-time obstacle avoidance.
- **Fall Detection & Alert System**: Sends alerts in case of unexpected falls.
- **Incline Detection**: Uses the MPU6050 sensor to measure the wheelchair's angle and adjust speed accordingly.
### Phase 2 (Planned Features)
- **Autopilot Mode**: Allows the wheelchair to autonomously navigate from point A to point B.
- **Path Learning**: The system learns and remembers frequently traveled paths.
### Phase 3 (Optional Enhancements)
- **Dash Cam Facility**: Records the wheelchair’s journey for security and review purposes.
## Technical Stack
- **Hardware**:
- Raspberry Pi 5 (for voice processing, sensor fusion, and motor control)
- ESP32 (for real-time motor control and sensor integration, coded in Arduino IDE using C++)
- Ultrasonic and IR sensors (for obstacle detection)
- Web Camera (for object detection and path understanding using YOLOv11, integrated with Raspberry Pi)
- MPU6050 (for incline detection and stability adjustments)
- Electric motors with speed regulation
- **Software**:
- Python (for voice command processing, AI/ML models, and system control)
- YOLOv11 (for real-time object detection and path understanding)
- Gemini API (for natural language understanding)
- Flask (for the Progressive Web App interface)
- MQTT (for communication between modules)
## How It Works
SWheels integrates multiple technologies to ensure seamless and intelligent mobility for users. Below is a breakdown of its core functionalities:
### 1. Voice and Joystick Control
- Users can issue voice commands like "move forward" or "turn left," which are processed using the **Gemini API** on Raspberry Pi.
- The joystick provides an alternative control mechanism for manual navigation.
### 2. Obstacle Detection and Avoidance
- A **web camera** captures real-time video, and **YOLOv11** detects objects such as doors, walls, and pathways.
- **Ultrasonic sensors** provide additional real-time distance measurements for close-range obstacle detection.
- The system fuses data from YOLOv11 and ultrasonic sensors to make precise navigation decisions.
### 3. Incline Detection and Speed Adjustment
- The **MPU6050 sensor** continuously monitors the wheelchair’s tilt and angle.
- If the system detects an incline or decline, it automatically adjusts motor speed for a safe and stable ride.
### 4. Autopilot Mode (Planned Feature)
- The system will use **path learning algorithms** to memorize frequently traveled routes.
- It will allow autonomous navigation from point A to point B, considering obstacles and terrain conditions.
### 5. Web Interface (PWA)
- A **Progressive Web App (PWA)** enables remote monitoring and control.
- Users can access wheelchair diagnostics, battery status, and navigation logs.
## Setup & Installation
### Hardware Setup
1. Assemble the motors, sensors, and microcontrollers as per the provided circuit diagrams.
2. Flash the ESP32 firmware using PlatformIO or Arduino IDE.
3. Set up Raspberry Pi 5 with PiOS and install the required dependencies.
## Contributing
We welcome contributions! If you'd like to contribute, follow these steps:
1. Fork the repository
2. Create a new branch (`feature-new-functionality`)
3. Commit your changes
4. Push to your branch and submit a pull request
## License
This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
## Contact
For any questions or collaborations, feel free to reach out:
- GitHub: [your-username](https://github.com/your-username)
- LinkedIn: [Joshua Johnson](https://www.linkedin.com/in/joshua-johnson-63b560253/)