Understanding SLAM Using Pose Graph Optimization | | Autonomous Navigation, Part 3
Watch the other videos in this series:
What Is Autonomous Navigation?: https://youtu.be/Fw8JQ5Q-ZwU
Understanding the Particle Filter: https://youtu.be/NrzmH_yerBU
This video provides some intuition around Pose Graph Optimization—a popular framework for solving the simultaneous localization and mapping (SLAM) problem in autonomous navigation.
We’ll cover why uncertainty in a vehicle’s sensors and state estimation makes building a map of the environment difficult and how pose graph optimization can deal with it. We’ll also briefly cover occupancy grid maps as one way to represent the environment model.
Additional Resources:
- Implement Simultaneous Localization and Mapping (SLAM) with MATLAB: https://bit.ly/2Yk9agi
- Download ebook: Sensor Fusion and Tracking for Autonomous Systems: An Overview: https://bit.ly/2YZxvXA
- Download white paper: Sensor Fusion and Tracking for Autonomous Systems - https://bit.ly/3dsf2bA
- SLAM Course - 15 - Least Squares SLAM - Cyrill Stachniss video: https://youtu.be/VRGOLRGwAjg
- Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age. Paper by Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose ́ Neira, Ian Reid, John J. Leonard. - https://arxiv.org/abs/1606.05830
- Simultaneous Localisation and Mapping (SLAM): Part I. Paper by H. F. Durrant-Whyte and T. Bailey. IEEE Robotics and Automation Magazine, 13(2):99–110, 2006. - https://ieeexplore.ieee.org/document/1638022
- Simultaneous Localisation and Mapping (SLAM): Part II. Paper by T. Bailey and H. F. Durrant-Whyte. Robotics and Autonomous Systems (RAS), 13(3):108–117, 2006. - https://ieeexplore.ieee.org/document/1678144
--------------------------------------------------------------------------------------------------------
Get a free product trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See what's new in MATLAB and Simulink: https://goo.gl/pgGtod
© 2020 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
Видео Understanding SLAM Using Pose Graph Optimization | | Autonomous Navigation, Part 3 канала MATLAB
What Is Autonomous Navigation?: https://youtu.be/Fw8JQ5Q-ZwU
Understanding the Particle Filter: https://youtu.be/NrzmH_yerBU
This video provides some intuition around Pose Graph Optimization—a popular framework for solving the simultaneous localization and mapping (SLAM) problem in autonomous navigation.
We’ll cover why uncertainty in a vehicle’s sensors and state estimation makes building a map of the environment difficult and how pose graph optimization can deal with it. We’ll also briefly cover occupancy grid maps as one way to represent the environment model.
Additional Resources:
- Implement Simultaneous Localization and Mapping (SLAM) with MATLAB: https://bit.ly/2Yk9agi
- Download ebook: Sensor Fusion and Tracking for Autonomous Systems: An Overview: https://bit.ly/2YZxvXA
- Download white paper: Sensor Fusion and Tracking for Autonomous Systems - https://bit.ly/3dsf2bA
- SLAM Course - 15 - Least Squares SLAM - Cyrill Stachniss video: https://youtu.be/VRGOLRGwAjg
- Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age. Paper by Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose ́ Neira, Ian Reid, John J. Leonard. - https://arxiv.org/abs/1606.05830
- Simultaneous Localisation and Mapping (SLAM): Part I. Paper by H. F. Durrant-Whyte and T. Bailey. IEEE Robotics and Automation Magazine, 13(2):99–110, 2006. - https://ieeexplore.ieee.org/document/1638022
- Simultaneous Localisation and Mapping (SLAM): Part II. Paper by T. Bailey and H. F. Durrant-Whyte. Robotics and Autonomous Systems (RAS), 13(3):108–117, 2006. - https://ieeexplore.ieee.org/document/1678144
--------------------------------------------------------------------------------------------------------
Get a free product trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See what's new in MATLAB and Simulink: https://goo.gl/pgGtod
© 2020 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
Видео Understanding SLAM Using Pose Graph Optimization | | Autonomous Navigation, Part 3 канала MATLAB
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Path Planning with A* and RRT | Autonomous Navigation, Part 4Graph-based SLAM using Pose Graphs (Cyrill Stachniss)Simultaneous Localization and Mapping (SLAM)Lidar vs Vslam (cameras vs lasers) For Robot Vacuums - Which One is Best?Understanding Sensor Fusion and Tracking, Part 1: What Is Sensor Fusion?Autonomous Navigation Mobile Robot using ROS | Jetson Nano | RPLidar | Differential Drive KinematicsVisual Inertial Simultaneous Localization and Mapping (VISLAM) IntroductionGetting Started with LIDARIs LIDAR easy to use for hobbyists? DIY Roomba? Obstacle Avoidance System for RoboticsUnderstanding the Particle Filter | | Autonomous Navigation, Part 2simulating a LIDAR sensor from scratch with python | SLAM SERIESVisual SLAM (indoor and outdoor)SLAM-Course - 01 - Introduction to Robot Mapping (2013/14; Cyrill Stachniss)What Is Autonomous Navigation? | Autonomous Navigation, Part 1Meet Spot, the robot dog that can run, hop and open doors | Marc RaibertUnderstanding Sensor Fusion and Tracking, Part 2: Fusing a Mag, Accel, & Gyro EstimateSLAM-Course - 03 - Bayes Filter (2013/14; Cyrill Stachniss)Customize Your Object DisplayFactor Graphs and Robust Perception | Michael Kaess | Tartan SLAM Series