NitinJSanket/ESE650Project2

ESE 650: Learning in Robotics, Project 2, Panorama Stitching using Orientation tracking based on Unscented Kalman Filter

Unscented Kalman Filter based Orientation tracking for Panorama Stitching

Problem Statement

Given data from an IMU (accelerometer and gyroscope), estimate the 3D orientation and use this information to stith a panorama.

Usage Guide:

1. Run Wrapper.m for running Complementary Filter, Kalman Filter and Unscented Kalman Filter.
2. Change the flags in Wrapper.m as needed.
3. By default, the code runs all the filters, shows the panorama stitching and saves the panorama in the current directory.
4. By default, image blending is off as it is very slow, use Wt to turn it on.
5. When you run the code, dialog boxees will open for you to load the necessary files. General order is IMUData, ViconData and then CameraData (as the flags are set).
6. Rotplot is disabled by default, enable it using the RotboxFlag in Wrapper.m

Report:

You can find the report here.

Rotplot outputs for attitude estimation:

Sample Panorama Stitching Output:

References:

For UKF:

1. Kraft, Edgar. "A quaternion-based unscented Kalman filter for orientation tracking." Proceedings of the Sixth International Conference of Information Fusion. Vol. 1. 2003.
2. S. J. Julier and J. K. Uhlmann, A new extension of the Kalman filter to nonlinear systems , in International Symposium on Aerospace/Defense Sensing, Simulation and Controls, Orlando, USA, 1997.

For Panorama Stitching:

3. http://www.csie.ntu.edu.tw/~cyy/courses/vfx/05spring/lectures/handouts/lec06_stitching_4up.pdf
4. http://cs.gmu.edu/~kosecka/cs482/lect-panoramas.pdf

Complementary Filter:

5. http://www.pieter-jan.com/node/11

Kalman Filter:

6. MEAM 620 slides at https://alliance.seas.upenn.edu/~meam620/wiki/index.php?n=Main.Schedule2015?action=download&upname=2015_extendedKalmanFilter.pdf