FYP Progress for Week 1 & 2

Overview

For the past two week, the main focus has been trying to understand the literature's received from seniors, Wang Fei and Cui Jinqiang.
I have also downloaded and installed MatLab on my PC and labtop, so that whne I finish reading, I could getting started with the Matlab codes.

 Classification of Literature

The literature's can be roughly classified into following topics:

• Localisation
• Feature based localisation
• Feature extraction
• Cartesian coordinate based
• Sensor coordinate based
• Transformation estimation
• Point based localisation
• ICP algorithm
• MbICP Algorithm
• IDC algorithm
• SLAM
• EKF SLAM
• Fast-EKF SLAM

Literature Summaries

Simultaneous Localisation and Mapping with extended Kalman Filter

This article introduced the steps of implementing a EKF-SLAM algorithm after processing the raw scanning data.
In the article, how to extract feature, and how to estimate the position of the UAV are not mentioned.

An Introduction to Kalman Filter (Find through Library E-resources)

As I had never came across the term EKF. I searched for this article so that I know how Kalman Filter and Extended Kalmen Filter came about.
This article explained in detail, how KF and EKF are obtained mathematically and illustrated what should be done, in updating an estimation after each set of data in obtained from measurement.

Stochastic models, estimations, and control <chap 1-3> (Borrowed from Library)

I browsed thought the first a few chapters of this book mainly to familiarise myself to matrixes.
I never came across Matric-Representation of linear systems and Correlation matrixes. I need to get a taste of what are the meanings of these matrixes.

High-speed laser localisation for mobile robots (Find through Library e-resources)

This paper presented a localisations method based on both sensor's coordinates and Cartesian coordinates. The algorithm is termed "HAYAI".
The proposed algorithm made use of linear filters, which could be easily implemented by Matrix multiplications. As a result, it achieved good computational speed with reasonable accuracy.

Feature-based laser scan matching for accurate and high speed mobile robot localisation

This paper aimed to improve on the accuracy of HAYAI algorithm by refining the feature extraction part of the HAYAI algorithm.
Author Incorporated the covariance into the computation, which makes the process slower but more rigorous.
The line extraction and corner extraction algorithm has been improved to expect better accuracies.

Metric-Based Scan Matching Algorithms for Mobile Robot Displacement Estimation

This paper introduced the MbICP algorithm.
The introduced algorithm tried to solve for displacement and rotation at the same time. After taking approximation, the expression is simplified into second order equations, for which the extreme value can be easily obtained. The same was applied again for point -to-line transformation.
Author claims this method has significantly better result, as compare to tranditional ICP methods
.

Efficient Variants of the ICP algorithm [have not understood fully, in progress]

I am still working on this paper.
This is a review type of paper, therefore, I need to dig through some of the reference list before I could understand what all the comparisons are talking about.