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Intro to Autonomous Mobility Training Course

Up to 50% of the Students Will Receive Immediate Paid Internships.
90% Placement Rate In The Last 3 Years

LHPU provides high-quality, industry relevant training to engineers looking to start or advance their career in the automotive industry. Now, LHPU will be looking to also provide high-quality, industry relevant internships to engineers that complete one of our six-week bootcamps!

Ask Our Counselors Any Questions Here, No Obligation.


Only $25 a Month*

*LHPU has formulated a program that allows you to take our class for only $25.00 a month until you are placed into a job. Once you are placed, you can begin your payment program to pay for the course. Tuition funding assistance may be available.

About The Course:

Learn the basics of Perception, Localization, Control, and Technology Integration - Drive into the future of transportation with LHPU’s immersive Intro to Autonomous Mobility training.

If you have ever been told you do not have enough hands-on experience to be considered for a job role, you are not alone.  Lack of relevant, hands-on experience is the number one reason that an engineering candidate receives rejection.  LHPU training offers a solution to this problem.  In addition to industry relevant, hands-on training, LHPU has an internship program where alumni may be awarded the opportunity for subsequent hands-on experience through research and development projects.  Apply what you learn in a six-week bootcamp course during an internship and have additional valuable experience to show on your resume and speak of in an interview! 

Student Testimonial

Listen to one of our Alumni Graduates as she discusses her journey through the course into job placement by LHPU.

Course Modules:

Below is the structure of the course that you will be taking.

Module 1: Learn about Robot Operating Systems (ROS) and how it provides a flexible and unified software environment.  Then get the basics on Python programming language, the most popular and fastest growing language used in programming autonomous vehicles.  Become proficient in CAN J1939 Standard, and develop an understanding of how it enables data sharing and transfer for autonomous vehicles.  You will then start your work with sensors learning about Sonar and how to program the device and manage signal processing.  Finally, you will learn about the industry leading simulation software CarSim, by Mechanical Simulation Corporation, which you will use throughout this course.

Module 2, 3, & 4: Learn how LiDAR, Radar, and Computer Vision acts as an eyes of the self-driving vehicles providing them a 360-degree view, proximity localization, and detection of static and dynamic objects.  You will spend time processing signals from LiDAR, Radar, and Computer Vision hardware on workbenches, while receiving one-on-one instruction from our experienced trainers.

Module 5: Learn how machine learning and its various concepts are being used in autonomous vehicles. You will be mainly focusing on the deep learning aspect and how machine learning goes hand in hand with perception.  You will learn to use the power of machine learning techniques where OpenCV fails to work. You will focus on object recognition in real time scenarios. We will discuss the challenges faced for deep learning and how to solve them.  What you will do – Train your own machine learning model, integrate the machine learning model with ROS and the camera and use techniques learned from the previous modules and the results from the machine learning model to develop algorithms to control your autonomous vehicle.

Module 6: Gain an understanding of coordinate systems, map making, and necessary formulas.  Take a deep dive in the GNSS system and why it is a key enabler of Autonomous Mobility.  In this module you will analyze accuracy performance between standard and RTK enhanced GPS data, understand how to connect to a live GPS receiver stream and how to analyze this data. Analyze accuracy performance between standard and RTK enhanced GPS data, and collect GPS data from a full size autonomous electric vehicle as it maneuvers a course, also recording data from the second receiver and determine how it calculates orientation.

Module 7: Learn about Drive by Wire (DBW) and how it enables autonomous vehicles.  We will discuss how modern cars have assisted driving features in cruise control, Anti-lock brakes, traction control, and stability control. You will be introduced to throttle, brake, and steering actuators which are essential to autonomous vehicle operation.  Then work with actual DBW components on benches, learning about how the steering and braking mechanisms and actuators work.  Implement a simple steering angle controller (PID) to position the wheels, gathering data to manage both the position and the velocity of the steering angle. Then you will install your steering controller algorithm into an autonomous electric vehicle allowing it to either directly control the steering or run in "safe parallel" where it computes steering actuator commands that we compare to the vehicle’s commands.

Module 8: Here is where you bring it all together by creating models for Sensor Fusion, Path Planning, and Vehicle Control using MATLAB Simulink and CarSim.  We start with a dive into Kalman Filtering and then develop and demonstrate building of a IMU GPS filter structure and assess performance of the filter, using MATLAB control system and sensor fusion toolboxes.  You will learn discreet Path Planning and Prediction concepts, followed by Trajectory Generation, and finally you will generate you own path plan.  Then you will learn about closed-loop feedback controls, understanding the Model Predictive Control formulation, and finally gain the experience and knowledge of the integration and tuning of the advanced controls in the simulation environment, CarSim.

Module 9: You will apply all of your learning in the previous 8 weeks as part of a project team by tackling a tough challenge on one of our Autonomous Electric Vehicles.  Perhaps you will integrate a new sensor, such as LiDAR, onto the vehicle and have to create a path plan to enable autonomous functioning, or perhaps we will ask you to improve the machine learning functionality of the vehicle’s controller.  What ever the challenge, your learning  will culminate with an experience that you will not find in any other training program, one which you can use to communicate your grasp of Autonomous Mobility technologies in front of a hiring manager looking for someone with your newly acquired skills.  And don’t forget to mention your IEEE Certification for completing LHPU’s Intro to Autonomous Mobility training program.

Course Schedule:

Pontiac, Michigan - November 9 - December 17. 


This class is IEEE Certified

 

6-Week Full-Time Course

The full-time 6-week program is designed for anyone who is currently job searching, between jobs, or who has just finished a university degree. This program mimics a full-time, 9-5 work environment for participants to collaborate in teams to find effective solutions.

Students will perform Modules 1 – 6 over a 6-week, full-time Monday – Friday schedule.

We are looking to hire five engineering interns from the pool of students who enroll in the November Class. Watch the video to learn more.