SLAM Materials: Literature Collection

Mar 13, 2016

Contents

Introduction

This is collection of literature on SLAM (mainly Visual SLAM). Keep updating.

Books

  • Probabilistic Robotics by S Thrun, W Burgard, D Fox - 2005 - MIT press

  • State Estimation for Robotics by TD Barfoot - 2017

  • Multiple View Geometry in Computer Vision by A Harltey, A Zisserman - 2006 - Cambridge University Press

  • 视觉 SLAM 十四讲 by 高翔 etc - 2017 - 电子工业出版社

  • Estimation with Applications to Tracking and Navigation by Y Bar-Shalom, XR Li, T Kirubarajan

  • Optimal Estimation of Dynamic Systems, Second Edition by JL Crassidis, JL Junkins

Tutorials and Basics

  • SLAM Tutorial 1

  • SLAM Tutorial 2

  • Visual Odometry 1

  • Visual Odometry 2

  • Bundle Adjustment

  • A tutorial on graph-based SLAM

  • Motion and structure from motion in a piecewise planar environment

Parameterization

  • Inverse Depth Parametrization for Monocular SLAM

  • Pose parameterization using Lie groups

    • On-Manifold Preintegration for Real-Time Visual–Inertial Odometry

    • State Estimation for Robotics by TD Barfoot, Chapter 7.

  • Pose estimation using linearized rotations and quaternion algebra

Batch Optimization

  • g2o

  • Google Ceres Solver

  • GTSAM

  • SBA

  • Relative Bundle Adjustment

Graph SLAM

  • Olson 2006

  • Square Root SAM 2006

  • iSAM 2008

  • Gresetti 2009

  • iSAM2 2011

  • Johannsson 2013 Temporally scalable visual SLAM using a reduced pose graph

  • Survey of Geodetic Method for SLAM

  • Generalized graph SLAM: Solving local and global ambiguities through multimodal and hyperedge constraints

  • COP-SLAM: Pose Chain Graph

  • Towards a robust back-end for pose graph SLAM

Batch vs filter

  • The iterated Kalman filter as a Gauss–Newton method

  • Why filter?

  • Introduction part in OKVIS paper

Mapping

  • Robot Mapping: A Survey

Important SLAM Works

  • EKF Based: P. Newman’s group’s work

  • Partical Filter Based: FastSLAM

Impressive Visual SLAM Works

  • EKF - Sparse Feature Based

  • Keyframe Graph Optimization - Sparse Feature Based

  • Relocalization:

  • Keyframe Graph Optimization - Direct Dense Based

  • Direct Dense with Surface Construction

    • KinectFusion

Loop Closing

  • Appearance Based: Ulrich 2000

  • TREE-MAP: Frese 2006 Closing a Million-Landmarks Loop

  • Bags of Words Bases: Angeli 2008

  • Appearance Based: FAB-MAP 2008

  • Appearance Based: FAB-MAP 2.0 2010

  • Vocabulary tree

  • Bag of Binary Words Based 2011

  • Down-sampled Binarized Images Based: H. ZHANG 2014

  • Gist

    • implementation of gist

    • loop close with gist in in Manhattan World

  • Visual Place Recognition A Survey

State of Art Works

  • Direct dense method: LSD-SLAM

  • Semi-Direct method: SVO and SVO 2.0

  • Feature based method: ORB-SLAM

  • Direct sparse method: DSO

Visual Inertial SLAM

  • MSCKF

    • 1.0

    • 2.0 in Li’s dissersion: Visual-Inertial Odometry on Resource-Constrained Systems

  • Others from Mourikis and Li’s group:

    • Decoupled Representation of the Error and Trajectory Estimates for Efficient Pose Estimation

    • Vision-aided Inertial Navigation with Rolling-Shutter Cameras

    • Online Temporal Calibration for Camera-IMU Systems: Theory and Algorithms

  • Keyframe-based visual–inertial odometry using nonlinear optimization

  • ROVIO

  • Inertial ORB-SLAM

  • On-Manifold Preintegration for VIO

  • Asynchronous adaptive conditioning for visual–inertial SLAM

  • S. Jones IJRR 2010

  • Kelly IJRR 2011

  • A Hesch IJRR 2014

  • A Hesch TRO 2014

Fusing Odometry And Other Sensor into V-SLAM

  • Weighted Local BA

  • Fast Odometry Integration in Local Bundle Adjustment-Based Visual SLAM

  • Bi-Objective Bundle Adjustment with Application to Multi-Sensor SLAM

Combining More Image Information

  • combining visual SLAM and dense scene flow

  • Incorparating edges:

Semantic SLAM and Learning for SLAM

  • SLAM++

  • Special Issues IJRR on RSS 2014

  • Probabilistic Data Association for Semantic SLAM (Best Paper in ICRA-2017)

  • Learning for Localization and Mapping, workshop at IROS 2017

Slides

  • The Problem of Mobile Sensors (Workshop in RSS 2015)

  • From author of ORB-SLAM

Good blogs and discussions

  • The Future of Real-Time SLAM and “Deep Learning vs SLAM”

  • 半闲居士

  • 白巧克力亦唯心

  • 刚刚开始做机器人,打算做SLAM,不知道机器人定位领域现在有哪些比较新的算法?希望大家推荐推荐

  • 去美国读CS博士,方向是机器人导航,视觉方面,推荐一下相关编程方面准备?还有相关算法需要学习哪些?

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