Autonomous Vehicles:

By the end of this lecture, students will be able to:

1- Understand the core concepts of autonomous vehicles.
Explain what differentiates autonomous vehicles from traditional vehicles.
Identify and Describe Sensor Technologies

2- List the types of sensors utilized in autonomous vehicles.
Explain the role of each sensor and how they work together to create a comprehensive view of the vehicle's environment.
Comprehend the Necessity of Multiple Sensors

3- Understand the reasons for using multiple sensors in redundancy and data fusion.
Discuss how sensor diversity enhances reliability and safety.
Understand the Underlying Algorithms

4- Gain insight into the algorithms that govern autonomous vehicle behaviors.
Analyze how these algorithms process sensor data to make driving decisions.
Recognize Challenges in Autonomous Vehicle Development

5- Identify current technological and ethical challenges facing the development of autonomous vehicles.
Explore potential solutions to overcome these challenges.
Explore Software Modules Critical to Autonomous Operation

6- Understand the function of perception software in detecting and classifying objects.
Learn about the planning module that devises the vehicle's path and movements.
Examine SLAM technology and its importance in autonomous navigation.
Prepare for a Future in Autonomous Vehicle Technology

7- Discover the technical skills and knowledge base necessary for a career in the field of autonomous vehicles.
Understand the technologies and tools that are essential for anyone starting in this domain.
After attending this lecture, students will have a clearer understanding of the multifaceted nature of autonomous vehicles and the complexities involved in their operation. They will leave with the foundational knowledge required to pursue further study or a career in this cutting-edge field.

Date: Wednesday, November 15th at 10:00 a.m., US Eastern Time.
Topic: Robotics