With LHP’s immersive autonomous technologies training, engineers will learn the basics of Perception, Localization, Control, & Technology Integration and gain relevant hands-on skills that are lacking in today’s automotive landscape. LHP’s training helps build the skills and hands-on experience to develop a talent solution that addresses the autonomous revolution.
Through technical and personal skills development, LHP reduces the cost of acquisition and can upskill existing talent to address the increased skills needed for the advanced technology and the gap in capacity that will continue to grow through the changing automotive landscape.
Reduce the cost of acquisitions. Cost of acquisition $75k - $100k to train an engineer + 1 year to ramp up (recruiter, train, implement, interview...etc.) LHP can vet the talent and you can trust us on the correct hire.
Hands-on experience implementing and designing autonomous technology on a fully-electric vehicle, coupled with project management and workplace professional development.
LHP training Intro to Autonomous Mobility curriculum is approved through IEEE, "the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity."
With over 750 engineers trained and now in the automotive market, LHP’s training organization is a proven talent solution for OEMs, Tier 1, and Tier 2 suppliers.
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.
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.
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.
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.
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.
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.
As part of our training, LHP utilizes a fully Autonomous Electric Vehicle provided by our industry partner PerceptIn. It comes complete with a fully integrated sensor package that enables fully autonomous operation. It combines patented vision-based sensor fusion with a patented modular computing system to provide a safe and reliable method of transport in low-speed environments. It uses visual intelligence technology including a Global Navigation Satellite System (GNSS) module, sonar, and radar.
During the Intro to Autonomous Mobility Course, students will implement Sonar, Radar, LiDAR, and sensor technologies directly on the vehicle in order to demonstrate a fully-autonomous vehicle by the end of the 9 weeks.
