This 1-month beginner-level course provides a comprehensive introduction to robotics, covering fundamental concepts like robot anatomy, kinematics, dynamics, motion planning, and programming. Participants will gain hands-on experience with robotics simulation software (Gazebo, MATLAB) and Python programming for robotics, enabling them to design, simulate, and analyze robotic systems. The course also includes practical exercises, real-world applications, and a final project, ensuring a strong foundation in modern robotics principles.
Who Can Join?
Beginners interested in robotics
Engineering students (Mechanical, Electrical, Computer Science)
Hobbyists and tech enthusiasts
Why Take This Course?
Learn core robotics principles and programming
Gain hands-on experience with simulation tools
Work on real-world motion planning projects
What’s Included?
✅ Certificate of Completion
✅ Free Study Materials + Robotics Kit
✅ Live Interactive Classes
✅ Batch Access & Community Support
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Kickstart your robotics journey today!
This chapter provides a foundational understanding of robotics, covering its definition, key components, and real-world applications. It explores the historical evolution of robotics, from early mechanical automata to AI-powered intelligent systems. You'll learn about different types of robots, including industrial, medical, consumer, and autonomous robots, and their role in transforming industries. The chapter also discusses ethical considerations, such as job displacement, privacy, and the responsible use of robotics in society.
Robots use sensors to perceive their environment and gather data, such as detecting obstacles or measuring temperature. Actuators convert control signals into physical movement, often using motors like DC motors or servo motors to drive joints or wheels, enabling robots to interact with their surroundings. These components work together to enable precise and efficient robotic functions.
Robot anatomy refers to the structure and components that enable a robot to function, including its frame, joints, actuators, sensors, and end-effectors. These parts work together to allow movement, interaction with the environment, and task execution, all controlled by a central controller.
This lesson covers the basics of kinematics in robotics, focusing on forward and inverse kinematics. It explains how joint movements influence the position and orientation of the robot's end effector, essential for controlling and planning robot motion.
This chapter introduces control systems in robotics, focusing on PID (Proportional-Integral-Derivative) control, which is essential for ensuring precise and stable robot behavior. It explains the components of a control system, such as the input (setpoint), process (robot), output (actual value), and the controller, which adjusts the system to minimize error. The chapter delves into the role of feedback, types of control systems (open-loop, closed-loop, adaptive), and the importance of error correction mechanisms. It also covers the practical implementation of PID control, from sensor selection to parameter tuning, ensuring robots perform tasks accurately and efficiently.
This chapter introduces the fundamental principles of forward kinematics, which determines a robot's end effector position based on joint parameters. It covers coordinate frames, transformation matrices, and step-by-step forward kinematic calculations. By the end of the chapter, learners will understand how robotic arms move in space and how to compute their positions using mathematical models, forming the foundation for advanced robotics concepts.
This chapter covers the fundamental concepts of coordinate systems and transformations in robotics. It explores different coordinate frames, including Cartesian, cylindrical, and spherical systems, and their applications in representing spatial positions. The chapter also introduces transformation matrices, rotation operations, and homogeneous coordinates, which are essential for modeling robot motion and analyzing complex transformations. By mastering these concepts, readers will gain a strong foundation for solving kinematic problems, planning trajectories, and simulating robotic movements.
This chapter introduces the core concepts of 3D rotation, focusing on three main methods of representing orientation: rotation matrices, Euler angles, and quaternions. It explains how each method works, their mathematical foundations, advantages, and limitations. The chapter also covers how to perform and combine rotations, transform coordinate systems, and choose the right representation for robotic and 3D spatial tasks.
This chapter introduces homogeneous transformations, a mathematical tool used to represent both rotation and translation of objects in 3D space using 4×4 matrices. It explains how these transformations are crucial in robotics and computer graphics for modeling the position and orientation of objects or robotic parts. The chapter covers the structure of transformation matrices, how to apply them to points, and their role in forward kinematics. It also introduces Denavit-Hartenberg (DH) parameters for simplifying the modeling of multi-joint robotic arms and highlights the importance of these transformations in advanced spatial reasoning and robotic motion analysis.
This chapter introduces the basics of dynamics, focusing on the forces and torques that cause motion in mechanical systems. It covers key principles such as force and torque equations, energy conservation, dynamic system modeling, and mechanical interactions. The chapter highlights the importance of understanding how forces and torques affect motion, essential for designing and controlling robots and other mechanical systems.
This chapter introduces the fundamentals of motion planning in robotics, focusing on how robots determine safe and efficient paths from one point to another. It covers different types of motion (continuous vs. discrete, open-loop vs. closed-loop), motion planning in free vs. constrained environments, and key algorithms like A*, Dijkstra’s, BFS, and RRT. It also highlights important constraints such as velocity limits, obstacle avoidance, and workspace boundaries. Finally, it touches on path smoothing and trajectory planning to ensure smooth and feasible robot movements.
This chapter introduces grid-based planning, where the environment is divided into discrete cells to simplify robot navigation. It covers 2D and 3D grid representations, occupancy grids, and navigation maps used to define free and occupied spaces. Key pathfinding algorithms like A*, BFS, and Dijkstra’s are explained for navigating these grids. The chapter also discusses how to handle dynamic obstacles and the trade-offs between grid resolution and computational complexity in real-time robotic applications.
This chapter introduces the core concepts of Python programming essential for robotics. It covers basic constructs like data structures, loops, functions, and object-oriented programming, along with key libraries such as NumPy, Matplotlib, and ROS. The chapter also explores motion planning tools and simulation integration, enabling learners to write Python scripts for controlling robots and simulating robotic behavior effectively.
This chapter introduces the use of simulation software in robotics, focusing on how virtual environments are used to test and refine robot motion and path planning. Learners explore popular tools like Gazebo, CoppeliaSim, and Webots, and gain hands-on experience setting up robot models, sensors, and environments. The chapter covers motion planning algorithms, visualization of robot behavior, debugging techniques, and the critical transition from simulation to real-world deployment.
This chapter guides learners through the final stage of the course—building a complete robotic simulation project. It emphasizes applying all previously learned concepts such as motion planning, Python programming, and obstacle avoidance in a real-world scenario. Students will choose a robotic platform, define a task, implement path planning and control algorithms, test the system, and document the entire process. The chapter culminates in a hands-on, practical project that showcases their understanding and skills in robotics simulation and automation.
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