Robotics Course – godigitalsphere.com

Robotics Course

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Start Date:

05/04/2025

Duration:

32Month

Difficulty

Intermediate

Overview

This Robotics course is designed to equip you with the skills and knowledge required to understand, build, program, and control robots. You'll learn about the components, algorithms, and technologies used in modern robotic systems. The course offers both theoretical insights and practical experience, preparing you for a career in robotics, automation, AI, or related fields.

You’ll Learn

The fundamentals of robot design, programming, and control

Key robotic algorithms and sensor technologies.

ow robots can perform complex tasks in different environments.

The integration of AI and machine learning into autonomous robotic systems.

Practical experience in building and programming robots.

Autonomous Robotics and Artificial Intelligence

Robotics Applications and Future Trends

Course Structure

Module 1: Introduction to Robotics

Overview of Robotics: Understanding the role and importance of robotics in modern industries (e.g., manufacturing, healthcare, aerospace).
History and Evolution of Robotics: A look at key milestones in robotics and its development.
Types of Robots: Industrial robots, autonomous robots, service robots, and medical robots.
Core Components of Robots: Basic hardware (sensors, actuators, controllers) and software (algorithms, control systems).
Applications of Robotics: How robots are used in various industries and their impact.

Module 2: Robotic Kinematics and Dynamics

Understanding Robot Motion: Basic principles of robot movement, including joint and end-effector motions.
Forward and Inverse Kinematics: Calculating the position of robot arms (forward) and determining the joint angles for a desired end-effector position (inverse).
Trajectory Planning: Techniques for planning and controlling the path of a robot.
Robot Dynamics: How forces and torques are applied to move robots.
Degrees of Freedom: Understanding how multiple joints allow for versatile movements.

Module 3: Sensors and Actuators in Robotics

Sensors: Introduction to common sensors used in robotics such as vision sensors, proximity sensors, force sensors, and accelerometers.
Actuators: Overview of motors and actuators that control robot movement, including electric, pneumatic, and hydraulic actuators.
Sensor Integration: How sensors and actuators work together to create precise robot control.
Sensor Fusion: Combining data from multiple sensors to improve decision-making and enhance robot capabilities.

Module 4: Control Systems for Robots

Control Systems Basics: Introduction to control theory, including open-loop vs. closed-loop systems.
PID Control: Proportional-Integral-Derivative (PID) controllers used for precise movement and feedback.
Motion Control: Controlling robot speed, positioning, and path.
Path Planning and Navigation: Algorithms used for robots to navigate around obstacles and follow paths.
Robot Operating System (ROS): Introduction to ROS, a popular platform for developing robotic applications and controlling hardware.

Module 5: Robot Programming and Algorithms

- Autonomous Systems: Principles of robots that operate independently, such as self-driving cars, drones, and mobile robots.
- AI in Robotics: How machine learning, deep learning, and reinforcement learning are applied to autonomous robots.
- Robot Vision: Using cameras and deep learning to recognize objects and interpret visual data.
- Simultaneous Localization and Mapping (SLAM): Algorithms that allow robots to map their environment and localize themselves simultaneously.
- Real-World Applications: Autonomous robots in industries such as logistics, healthcare, and defense.

Module 6: Autonomous Robotics and Artificial Intelligence

Autonomous Systems: Principles of robots that operate independently, such as self-driving cars, drones, and mobile robots.
AI in Robotics: How machine learning, deep learning, and reinforcement learning are applied to autonomous robots.
Robot Vision: Using cameras and deep learning to recognize objects and interpret visual data.
Simultaneous Localization and Mapping (SLAM): Algorithms that allow robots to map their environment and localize themselves simultaneously.
Real-World Applications: Autonomous robots in industries such as logistics, healthcare, and defense.

Module 7: Robotics Applications and Future Trends

Industrial Applications: Robots used in manufacturing, assembly, quality control, and packaging.
Medical Robotics: Robots used for surgeries, prosthetics, rehabilitation, and assistive devices.
Robots in Hazardous Environments: How robots are used for tasks like bomb disposal, space exploration, and underwater exploration.
Ethical Considerations: The social and ethical implications of robotics, such as job displacement and robot decision-making.
The Future of Robotics: Emerging trends like soft robotics, collaborative robots (cobots), and the integration of AI into robotics.

Final Assessment

Quiz / Multiple Choice Questions
Practical Scenarios & Case Studies
Certificate of Completion

Instructor

Kathleen Grant (Demo)

This course is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python. The fact is, Python is one of the most popular programming languages in the world – Huge companies like Google use it in mission critical applications like Google Search. And Python is the number one language choice for machine learning, data science and artificial intelligence. To get those high paying jobs you need an expert knowledge of Python, and that’s what you will get from this course. By the end of the course you’ll be able to apply in confidence for Python programming jobs. And yes, this applies even if you have never programmed before. With the right skills which you will learn in this course, you can become employable and valuable in the eyes of future employers.