As the field of automated driving evolves, the need for highly reliable perception systems becomes increasingly critical, particularly at higher levels of automation. Lidar (Light Detection and Ranging) technology has emerged as a vital component of modern automated driving systems, owing to its ability to provide accurate, high-resolution, and real-time detection and measurement of surrounding objects.
In this webinar, we will discuss how to build lidar based development workflows for perception and navigation in autonomous driving application, covering the critical stages of data acquisition, processing, and interpretation.
In this webinar you will gain insights on:
• Accessing and streaming lidar data
• Simulating lidar sensor in synthetic environments
• LIDAR camera cross calibration
• Apply deep learning algorithms on lidar point cloud
Mr. Minhaj Palakkaparambil Mohammed is a product manager at Math Works, with a focus on autonomous systems and lidar point cloud processing. Prior to joining Math Works, he worked as a lead engineer for developing autonomous systems. He holds a master’s degree from NIT Suratkal in India.
Senior Application Engineer at Mathworks
Sumit Garg is a senior application engineer at MathWorks India specializing in design analysis and implementation of radar signal processing and data processing applications. He works closely with customers across domains to help them use MATLAB® and Simulink® in their workflows. He has over nine years of industrial experience in the design and development of hardware and software applications in the radar domain. He has been a part of the complete lifecycle of projects pertaining to aerospace and defense applications. Prior to joining MathWorks, he worked for Bharat Electronics Limited and Electronics and Radar Development Establishment as a senior engineer. He holds a bachelor’s degree in electronics and telecommunication from Panjab University, Chandigarh.