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Real-time path-planning from 3D reconstruction and depth estimation: an algorithm for calibrated stereo cameras.

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Stereo Camera Path-Planning

Description:

This program is for a stereo camera device, and enables real-time path planning and obstacle avoidance for robotic vehicles. The code implements OpenCV with Python for camera calibration, stereo correspondence, 3D reconstruction, and pathfinding.

Algorithm Procedure:

The input images are first rectified from camera calibration parameters before using OpenCV's StereoSGBM algorithm to compute the disparity map. The disparity map is then reprojected to a 3D space in the world coordinate system for obstacle filtering. Obstacles located above the floor plane are used to construct an occupancy grid. The A* pathfinding algorithm operates on the occupancy grid, with the end node determined by the furthest depth value with the shortest Euclidian distance from unified camera's principal point. The computed A* path is then back-projected to 2D image coordinates and overlaid on the unrectified left camera image.

Results:

Video demonstration:

https://youtu.be/Hd16ineBsT8

Screenshots:

Fig. 0

3D Scene Projection with Planned Path:

Fig. 4

Image of Stereo Camera Device:

Device Photo

System Diagram:

SBD

Core Dependencies:

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Real-time path-planning from 3D reconstruction and depth estimation: an algorithm for calibrated stereo cameras.

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