Design of a Portable Odometry System using Stereo Vision

Job Description:

design of a portable visual odometry system that utilizes a feature-based

stereo visual odometry, with IMU assistance. The focus is on developing an algorithm that can provide a usable level of accuracy, while still being possible to implement in a compact and ergonomic fashion. The system uses rectified and distortion-corrected images, and implements

a Harris-Stevens corner detection algorithm to detect landmarks. These landmarks are matched in successive frames using a KLT point-tracking algorithm. Stereo correspondences are found using an optimized block-matching algorithm using the normalized cross-correlation

metric. These disparity values are used to triangulate two-point clouds at successive steps in frames, after which a weighted least-squares pose estimation algorithm is run to estimate the pose change between timesteps. A multivariate gaussian anomaly detection algorithm is used to reject outliers due to poor matching or moving objects.

Finally, a Kalman filter is exploited to enforce a constant-acceleration dynamic model on the cameras, and fuse IMU data for better attitude estimation.

Skills: Algorithm, C Programming, C++ Programming, Matlab and Mathematica, Python

About the Client:
( 4 reviews ) Gloucester, Canada

Project ID: #36110377

11 freelancers are bidding on average $273 for this job


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