Bowen's Tech Blog

Talks about the future development directions of SLAM.

This post goes through the popular visual SLAM systems.

This post goes through the popular Visual Inertial SLAM systems, including MSCKF, OKVIS, VINS-Mono and etc.

This post talks about the theory for Visual Inertial SLAM. Notes of book SLAM in Autonomous Driving.

Majority content of this post came from the book Basic Knowledge on Visual SLAM: From Theory to Practice.

SLAM (Simultaneous Localization and Mapping) is the technique to establish the nearby environment and localize the moving object inside it at the same time according to sensor measurements. SLAM can be used in augmented reality, autonomous vehicles, and robot’s navigation. The mathematic theory of SLAM is the state estimation.

Visual SLAM is a kind of SLAM that depends on on visual sensors (cameras), which also involves photometric and geometric computer vision.

This post talks about the fundamental math for SLAM, including Homogeneous Coordinates, Transformation in 3D space, Probability, SVD, Least Square Optimization, Lie Group and Lie Algebra and etc.

This post is the notes of book “State Estimation for Robotics”, which talks about the state estimation math for SLAM.

This post organizes the resources that I used to learn SLAM, also serves as a reference to other post in this blog.

This post talks about the knowledge (grammar, concepts) of C++.

Templates for efficient programming.