Sensors Simulation for Autonomous Systems

Focused View

SimXai Academy

46:20

286 View

1. Introduction

1. Introduction.mp4

01:21

2. Course Content.mp4

01:28

2. Introduction to SimXai Sensors Simulation

1. SimXai Simulation.mp4

03:05

2. SimXai Light Version.mp4

00:27

3. Getting Started

1. Hardware & Software Requirement.mp4

00:10

2. Running AV Example.mp4

06:36

4. Radar

1. Radar Principles.mp4

03:30

2. Radar Simulation.mp4

04:17

5. LiDAR

1. LiDAR Principles.mp4

03:48

2. LiDAR Simulation.mp4

02:54

6. SimXai Scenario Editor

1. Module Content.mp4

00:43

2. Navigating the Editor.mp4

03:35

3. Placing Vehicles in the Scenario Editor.mp4

00:53

4. Refining Vehicle Behaviour.mp4

09:11

5. Tagging System.mp4

01:14

6. Scenario File Generation.mp4

01:07

7. Vehicle Trigger Boxes.mp4

02:01

Description

Sensors Simulation for Autonomous Systems using SimXai for Radar , Camera Lidar and Ultrasonics sensors using LabVIEW

What You'll Learn?

Learn how to simulate Radar , Camera and Lidar sensors for autonomous systems using SimXai simulator
Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data
Process raw lidar data using Velodyne sensors with filtering, segmentation, and clustering to detect other vehicles on the road
Analyze radar signatures to detect and track objects. Calculate velocity and orientation by correcting for radial velocity distortions, noise, and occlusions

Who is this for?

Sensor Fusion Engineer , Vehicle Test Engineer , ADAS/AV Function Owner

What You Need to Know?

Basic knowledge of Sensor Theory

More details

Description
Simulation is a key technology for developing, verifying and validating the behavior of highly automated vehicles in a variety of scenarios, environments, system configurations and driver characteristics. More and more engineers use this powerful technology in their daily work to solve multidimensional and interdisciplinary problems. Simulation is mainly used where classical experiments (under controlled conditions) are not possible due to the size, number and complexity or also because of the impact on the environment. The increasing product complexity of software-defined vehicles (SDV) and their mapping to digital twins (DT) also leads to deep supply chains in the simulation domain. To navigate this data ecosystem, it is not just about understanding the technology itself, but more importantly be able to confidently evaluate simulation models, methods and processes, know their limitations and optimize the relationship between business impact and resources used.

This course is designed to approach simulation-driven development of highly automated and self-driving cars from both a latest and a future technology perspective

Powered by NVIDIAÂ and Unreal Engine ,The course builds on standardization projects such as ASAM OpenX and covers software approaches to simplify participants' entry into the technology area

Modules
A - Sensors Simulation (Radar , Camera , Lidar , Ultrasonic Sensors)
B - Scenarios & Driving Functions ( ASAM OpenDrive , ASAM OpenScenario )

Who this course is for:
Sensor Fusion Engineer , Vehicle Test Engineer , ADAS/AV Function Owner

User Reviews

Rating

average 0

Total votes0

Focused display

SimXai Simulation is an multi-platform desktop application used to simulate robots. It provides a complete development environment to model, program and simulate robots.It has been designed for a professional use, and it is widely used in industry, education and research.Simulation is a key technology for developing, verifying and validating the behavior of highly automated vehicles in a variety of scenarios, environments, system configurations and driver characteristics. More and more engineers use this powerful technology in their daily work to solve multidimensional and interdisciplinary problems. Simulation is mainly used where classical experiments (under controlled conditions) are not possible due to the size, number and complexity or also because of the impact on the environment. The increasing product complexity of software-defined vehicles (SDV) and their mapping to digital twins (DT) also leads to deep supply chains in the simulation domain. To navigate this data ecosystem, it is not just about understanding the technology itself, but more importantly be able to confidently evaluate simulation models, methods and processes, know their limitations and optimize the relationship between business impact and resources used.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.