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Model Predictive Controls for Autonomous Driving

A 3 month course on model predictive controls for autonomous driving.

Book a Class, for FREE

RELATED RECENT PLACEMENTS

Kirankrishna M

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SDM Institute of Technology Institute of technology in Ujire, Karnataka

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Swami Vivekananda Institute of Science & Technology

ARJUN PP

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Government Polytechnic College Kannur Polytechnic college in Kerala

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KLE Polytechnic Bailhongal

Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

  • The students will have a thorough knowledge of Model Predictive Controls for Autonomous Driving Vehicles and ADAS systems.
  • They can specialize in the domain and gain in-depth knowledge of it.
  • The students are exposed to the modern trends & the standard practices being followed in the industry right now.
  • After completing this course, the students will gain a better understanding of the concepts of Linear Algebra, Controls, Optimization using MPC for diverse problems in ADAS/AD motion planning.
  • Also, the course delves deep into the concepts of "Linearization of nonlinear motion models", "How to use an Optimization Solver" and "Step-by-step approach in building an MPC".

Course Syllabus

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week 1 - Introduction to Linear Algebra and Controls

  • Linear Algebra Refresher
  • Basics of Controls

Week 2 - Motion Models for Autonomous Driving

  • Motion Models
  • Lateral and Longitudinal Dynamics

Week 3 - Getting a Hold on LQR for Goal Reaching

  • Linear Quadratic Regulator
  • Problem Formulation
  • Stability and Controllability of LQR
  • Convergence of LQR
  • Using LQR and Motion Model for a goal-reaching problem

Week 4 - Introduction to Convex and Non Convex Optimization

  • Basics of Convex Optimization
  • Introduction to Non-Linear Cost Function

Week 5 - Introduction to MPC

  • Introduction to MPC
  • Feedback in Optimal Control
  • The Specialty of MPC’s Model
  • Structure of LQR and What MPC Adds to it?
  • Online Feedback

Week 6 - MPC for Goal Reaching Problem

  • Sequential Quadratic Programming
  • Tutorial on CVX_OPT
  • Coding MPC
  • MPC for Multiple-step Problem

Week 7 - Constrained MPC

  • QP to MPC
  • Constraints of MPC
  • Static Obstacle Avoidance - Theory

Week 8 - MPC for Collision Avoidance

  • MPC for a Static Obstacle in Practice
  • Multiple Static Obstacle Condition
  • MPC for Dynamic Obstacles
  • Adding Pedestrians to Constraints

Week 9 - Lateral Conditions of MPC

  • Lane Keeping Constraints in MPC
  • Lane Change condition

Week 10 - Uncertainty in MPC

  • Adding Uncertainty to a Motion Model
  • Types of MPC and Different Cost Formulations

Week 11 - Setting Up CARLA Simulator

  • Setting up CARLA
  • Using CARLA to run a small client-server controller
  • Testing PID in CARLA

Week 12 - Future Scope of MPC

  • Future Scope of MPC
  • MPC with Deep Learning Approach
  • Details on Project Implementation

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Formulating MPC for Non-Holonomic Motion Model

A project on implementing the Model Predictive Control for Non-Holonomic motion model using Python. The project involves formulating the cost function using the CVXOPT framework.

Implementing MPC in CARLA Simulator

Implementing obstacle avoidance, lane change, and lane-keeping checks in the CARLA simulator. The controller script should be implemented in the client-server model, to evaluate the control inputs for the next timestep.

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.8

Flexible Pricing

Talk to our career counsellors to get flexible payment options.

Premium

INR 40,000

Inclusive of all charges


Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals

  • 5 Years Accessto Skill-Lync’s Learning Management System (LMS)

  • Personalized Pageto showcase Projects & Certifications

  • Live Individual & Group Sessionsto resolve queries, Discuss Progress and Study Plans.

  • Personalized & Hands-OnSupport over Mail, Telephone for Query Resolution & Overall Learner Progress.

  • Job-Oriented Industry Relevant Curriculumavailable at your fingertips curated by Global Industry Experts along with Live Sessions.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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4 years in the experience range

Instructors with 4 years extensive industry experience.

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Areas of expertise

  • Autonomous Vehicle Controls

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