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Visual SLAM Module

This module implements Visual SLAM (Simultaneous Localization and Mapping) supporting monocular, stereo, and RGB-D camera inputs. It combines visual odometry and mapping in real-time to track camera motion and build a 3D map of the environment.

Features

  • Support for multiple camera types:
    • Monocular camera
    • Stereo camera
    • RGB-D camera
  • Feature detection and tracking using optical flow
  • Visual odometry using essential matrix or homography decomposition
  • 3D mapping using triangulation
  • Real-time trajectory visualization
  • Support for keyframe selection
  • 3D point cloud visualization

Requirements

Install the required dependencies:

pip install -r requirements.txt

Usage

Basic usage example:

from visual_slam import CameraParams, VisualSLAM

# Initialize camera parameters
camera_params = CameraParams(
    fx=525.0,  # focal length x
    fy=525.0,  # focal length y
    cx=320.0,  # principal point x
    cy=240.0,  # principal point y
    baseline=0.075  # for stereo setup
)

# Create SLAM instance
slam = VisualSLAM(camera_params)

# Process frames
pose, map_points = slam.process_frame(frame)

# Visualize results
slam.visualize()

Demo

Run the included demo script to test Visual SLAM with your camera:

python visual_slam.py

Components

  1. FeatureTracker: Handles feature detection and tracking between frames
  2. VisualOdometry: Estimates camera motion using epipolar geometry
  3. Mapping: Performs 3D reconstruction using triangulation
  4. VisualSLAM: Main class that integrates all components

Notes

  • Adjust camera parameters according to your specific camera setup
  • For best results, ensure good lighting conditions and textured scenes
  • The system performs better with slower, smooth camera motion