refslam.git - Refslam. SLAM code from Masters thesis

Age	Commit message (Collapse)	Author
2017-03-25	Add Feature method to test if in FOV	Martin Miller
	Added a boolean function that returns if the feature is in the FOV. This method does not use the camera calibration, it just tests if the feature's angle w.r.t. the body.
2017-03-25	Add Feature::dx()	Martin Miller
	This function allows an incremental update of the feature state where X += dx
2017-03-25	Add Feature methods.	Martin Miller
	Added a method to test if a feature is sane. It looks to see if the feature has negative depth or if it is too close or too far away. Added a method to output the feature location as a UTM struct.
2017-03-24	Move feature depth calculation to Feature class.	Martin Miller
	And also fixed F computation for features. I realized that the features were transformed from image to body frame prior to being passed to State. This makes sense because the State really doesn't need to know about Camera objects. Since the camera was no longer necessary inside of State it made sense to move the depth computation from Camera::ref2body() into a method in the Feature class that does not rely on camera parameters. Additionally, the depth solver was changed from a simple matrix inversion to a least squares calculation. Fx in the feature class was fixed to take into account dt. Updating Pkk1 is in the process of being modified to handle features.
2017-03-22	Add feature handling to state	Martin Miller

2017-03-20	Fix Jacobian of motion model.	Martin Miller
	This fixes a bug that was present in the pyslam code. The Jacobian of the motion model needs to be replaced with: F = I + F*dt
2017-03-19	Add feature Constructor	Martin Miller

2017-03-19	Add Feature::S() method.	Martin Miller
	This is a method for computing S for an independent measurement. It can provide a speed improvement over computing a full, correlated S, but may reduce quality if correlated measurements are treated as independent.
2017-03-19	Add motion model.	Martin Miller
	The motion model is broken into two parts, the creation of the L matrix and the state update. This means that ydot can be computed from the state object for many features at once, saving computation time.
2017-03-19	Implement feature measurement prediction.	Martin Miller
	Used a slightly simplified expression to compute pib0. Replaced the Householder Transform with quaternion based reflection (untested).
2017-03-18	Start Feature::h() method	Martin Miller

2017-03-18	Add Feature class	Martin Miller