Overview
Visual navigation is the key technology for drones to achieve positioning in GPS-denied environments. In this project, you will learn how to use camera optical flow data for indoor positioning.
What You’ll Learn
- Computer vision basics
- Optical flow algorithms
- Visual Inertial Odometry (VIO)
- Sensor fusion
Materials Needed
| Item | Quantity | Notes |
|---|---|---|
| ESP32-S3 Drone | 1 | - |
| OV2640 Camera Module | 1 | - |
| PMW3901 Optical Flow Sensor | 1 | Optional |
Step 1: Hardware Wiring
- OV2640 Camera → ESP32-S3 DVP interface
- PMW3901 (optional) → ESP32-S3 SPI interface
Step 2: Open the Project
Extract optical_flow.zip and open with VS Code.
Step 3: Implement Optical Flow Calculation
Open optical_flow.c and implement optical flow calculation:
void optical_flow_calculate(uint8_t* prev_frame, uint8_t* curr_frame,
int width, int height, float* dx, float* dy) {
// 1. Extract feature points (corners)
FeaturePoint features[100];
int feature_count = extract_corners(prev_frame, width, height, features, 100);
// 2. Track feature points
FeaturePoint tracked_features[100];
int tracked_count = track_features(prev_frame, curr_frame, width, height,
features, feature_count, tracked_features);
// 3. Calculate average displacement
*dx = 0;
*dy = 0;
for (int i = 0; i < tracked_count; i++) {
*dx += tracked_features[i].x - features[i].x;
*dy += tracked_features[i].y - features[i].y;
}
if (tracked_count > 0) {
*dx /= tracked_count;
*dy /= tracked_count;
}
}Step 4: Implement Visual Inertial Odometry (VIO)
Open vio.c and implement VIO:
void vio_update(float gx, float gy, float gz,
float ax, float ay, float az,
float dt, float flow_dx, float flow_dy) {
// 1. Predict position using IMU data
predict_position(gx, gy, gz, ax, ay, az, dt);
// 2. Correct position using optical flow data
correct_position(flow_dx, flow_dy, dt);
// 3. Output fused position
update_estimated_position();
}Step 5: Test
- Indoor flight, observe if the drone can maintain stable position (without GPS)
- Challenge: Draw a straight line on the ground and make the drone fly along it
Troubleshooting
Inaccurate optical flow calculation
- Improve lighting conditions
- Optimize feature point extraction algorithm
Position drift
- Adjust VIO parameters
- Add sensor fusion
Achievement
Congratulations! You have implemented visual navigation system, which is the key technology for drone positioning in GPS-denied environments!
Next Steps
In the next project, you will learn how to use A* algorithm for drone autonomous path planning.