Master's Certification Program in Autonomous Vehicles
- Offered bySkill Lync
Master's Certification Program in Autonomous Vehicles at Skill Lync Overview
Duration | 12 months |
Total fee | ₹2.50 Lakh |
Mode of learning | Online |
Credential | Certificate |
Master's Certification Program in Autonomous Vehicles at Skill Lync Highlights
- Earn a certificate of completion from skill-lync
- Learn industry-relevant skills from technical experts
- Get a paid internship after completing the course
- Work on projects, publish to your profile and get hired in top companies
- Interaction with Industry Experts through webinars and weekend workshops
Master's Certification Program in Autonomous Vehicles at Skill Lync Course details
- Applying Computer Vision for Autonomous Vehicle
- Localisation, Mapping and SLAM
- Path Planning & Trajectory Optimization Using C++ & ROS
- Autonomous Vehicle Controls using MATLAB and Simulink
- The Master?s Program in Autonomous Driving introduced by Skill Lync covers a step by step formulation to understand the complete process in building an Autonomous Vehicle
- The program is divided into 4 modules, each of which is accompanied by projects that will give a better understanding to the students of what they are being taught
- The first module is on Applying Computer Vision for Autonomous Vehicles. Using computer vision, the vehicle avoids obstacles on the road
- The second module will focus on Localisation, Mapping and SLAM
- In the third module, we will discuss Path Planning & Trajectory Optimization Using C++ & ROS. Using path planning, the vehicle decides on the lane that it will pick to reach from point A to point B
- The fourth module of the program will introduce you to Autonomous Vehicle Controls using MATLAB and Simulink
- Course Fees for Premium version INR 35000 per month
- Basic and Pro courses are also available
- Course fees for Basic and Pro version INR 25000 per month & INR 30000 per month
Master's Certification Program in Autonomous Vehicles at Skill Lync Curriculum
Applying CV for Autonomous Vehicles
Introduction to Computer Vision
Image Processing Techniques ? I
Image Geometries and Camera
Motion Models
Trackers / Filters in Computer Vision
Image Recognition and Classification
Video Analysis and Image Segmentation
3D Vision
Computer Vision architectures and Frameworks
Data collection and Synthetic Data Generation
12 Capstone Project
Localization, Mapping, and SLAM
Introduction
Kalman Filters
Extended Kalman Filters, UKF
Particle Filter
Monte Carlo Localization
GNSS/INS Sensing for Pose Estimation
Camera and Lidar data fusion
Introduction to SLAM/ Mapping
Occupancy Grid Mapping
EKF Slam
FAST Slam
GRAPH Slam
Path Planning & Trajectory Optimization Using C++ & ROS
Introduction
Configuring Space for Motion planning
Random sampling-based motion planning
Robot Operating System
Motion planning with Non-holonomic robots
Mobile Robot collision detection
Hierarchical planning for Autonomous Robots
Trajectory planning
Planning Algorithm
Planning in unstructured environments
Reinforcement learning for planning
Conclusion
Autonomous Vehicle Controls using MATLAB and Simulink
Course Overview
Classical Controls Overview
Start of Project - Adaptive Cruise Control
Longitudinal Controller Design
Adaptive Vehicle Speed Control
Adaptive Cruise Control - ADAS Modeling
Adaptive Cruise Control
Improvement to Adaptive Cruise Control
Lateral Control Model
Continuation of Lane Centering Feature
Lane Centering Feature Modification
Major Project
Master's Certification Program in Autonomous Vehicles at Skill Lync Entry Requirements
- Prerequisites: Basic coding
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