RoboSupreme [Level - Master]

Learn how to build robots that can navigate and move on their own using SLAM, path planning, and advanced mapping techniques.

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₹ 800/class

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Course Description

Want to create robots that can move without human control? This course dives into autonomous robotics, where you’ll learn how robots perceive their surroundings and make navigation decisions independently. You’ll work with SLAM (Simultaneous Localization and Mapping), path planning, and LIDAR-based mapping to create self-driving robots. Using ROS and Gazebo simulations, you’ll build real-world projects that demonstrate how robots navigate complex environments. By the end of this course, you’ll have the skills to develop intelligent, autonomous robotic systems.

✅ What Will You Learn?

1. Perception and Environment Understanding

How Robots Perceive the World: Robots rely on sensors like LIDAR, cameras, and ultrasonic sensors to collect information about their surroundings. You’ll learn how to interpret this sensor data.

2. Navigation and Movement

Path Planning: Robots need to figure out how to move from one place to another while avoiding obstacles. You’ll learn about algorithms that help robots find the best path.

3. Real-World Applications

By the end of the course, you’ll understand how autonomous systems are used in industries like:

Transportation: Self-driving cars and drones
Warehousing and Logistics: Autonomous forklifts and delivery robots
Healthcare: Service robots in hospitals
Agriculture: Autonomous tractors and monitoring drones

What is Artificial Intelligence? How AI is Used in Robotics Overview of Machine Learning and Deep Learning Introduction to AI Tools: TensorFlow, OpenCV, and ROS

Understanding Machine Learning Algorithms Supervised vs. Unsupervised Learning Building and Training Your First Machine Learning Model Evaluating Model Performance

How Robots “See” the World Using Cameras and Sensors Image Processing with OpenCV Object Detection and Recognition Face Detection and Tracking

Introduction to Neural Networks and Deep Learning Building Convolutional Neural Networks (CNNs) Using Pre-trained AI Models for Faster Results Real-Time Object Detection with AI

Understanding Reinforcement Learning (RL) Concepts How Robots Learn by Trial and Error Training AI Agents in Simulations Implementing RL for Autonomous Decision-Making

How Robots Navigate Using AI Path Planning and Obstacle Avoidance Using AI for Simultaneous Localization and Mapping (SLAM) Implementing Autonomous Navigation with ROS

Build an Object Detection Robot with TensorFlow and OpenCV Create an Autonomous Path-Following Robot Using AI Develop a Smart Surveillance System with AI Monitoring Build a Reinforcement Learning Robot in a Virtual Environment

Choose a Project of Your Interest Receive Mentoring and Guidance Showcase Your AI-powered Robot Get Certified and Boost Your AI Robotics Portfolio

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School

₹ 500/class

Buy Now

₹ 800/class

Buy Now

Any Query?

Course Includes

Lectures

N/A Classes

Duration

N/A Hours

Level

Beginner

Language

English

Certificate

Yes

Course Includes

Lectures

10 Classes

Duration

N/A Hours

Level

Beginner

Language

English

Certificate

Yes

Learning Path

Beginner

Intermediate

Advanced

Master

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