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Lidar Data Processing for Autonomous Systems

 The introduction of low-cost lidar sensors has significantly impacted various industries, making lidar data processing technology more accessible and crucial for advancements in automated driving, robotics, and aerospace. This webinar is dedicated to exploring lidar data processing, pivotal for enhancing perception and navigation in autonomous systems. Participants will gain insights into leveraging lidar data processing for advanced workflows, essential for the development of autonomous technologies.


This webinar will cover both basic and advanced aspects of lidar data processing, providing participants with a comprehensive understanding of how to effectively utilize this technology. Key areas of focus will include:

- Reading and streaming point cloud data.

- Applying deep learning algorithms for object detection and semantic segmentation.

- Enhancing accuracy with cross calibration between lidar and camera sensors.

- Map generation and SLAM (Simultaneous Localization and Mapping).

- Object tracking through sequential analysis of lidar point cloud data.

By the end of this webinar, attendees will be well-versed in lidar data processing and its application in the development of cutting-edge autonomous systems.

Related Resources:

- Lidar Camera Calibration with MATLAB:

- How to Use the Lidar Viewer App in MATLAB:

- Getting Started with Lidar Acquisition in MATLAB:

- Getting started with Lidar Labeler App:   

 • Getting Started with Lidar Labeler App  

- What Is Lidar Toolbox?: https://youtu.beMe7ZGpjwboA


00:00 Introduction

01:16 Object Detection and Tracking

03:00 Types of Lidar Point Clouds

04:50 How to Read Point Cloud Data into MATLAB

09:45 Semantic Segmentation of Lidar Data

13:00 C++ and CUDA Code Generation from Lidar Data Processing Algorithms

14:10 Lidar SLAM

17:55 What is Point Cloud Registration?

21:50 Colored 3D Point Cloud Creation using Ground Robots

23:40 What is Lidar Camera Calibration?

25:09 Project Camera Data on Lidar Data

27:30 Summary 

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