
Explore robot configurations used in industry, from cartesian and cylindrical to spherical, articulated, scara, and delta, detailing joints, degrees of freedom, and motion types.
Identify the difference between active joints driven by actuators and passive joints moved by external forces, with active joints powered by servo or stepper motors and passive joints like hinges.
Explore end effectors for robotic arms, including grippers, tools, sensor-based and vision-based systems, hybrid end effectors, and bioinspired options like octopus-inspired soft grippers.
Explore online versus offline robot programming, including teach pendant, lead-through, and playback methods, and offline simulation with text-based coding for domains like welding, polishing, and automation.
Compare extrinsic and intrinsic Euler angles, illustrating fixed-axis rotations (phi about x, theta about y, psi about z) versus rotating-axis conventions like zxz in robotics.
Derive the final rotation matrix for xyz intrinsic Euler angles by multiplying Rx(phi), Ry(theta), and Rz(psi), illustrating axis-specific rotations and the pitch, yaw convention.
Learn how to transform from frame i-1 to frame i using the Denavit-Hartenberg parameters, linking theta, d, a, and alpha to compute the end-effector pose.
Apply the modified denavit-hartenberg transformation from frame i-1 to i using rotation about x, translation along x, rotation about z, and translation along z to build a 4x4 homogeneous matrix.
Set all joints to zero to define the home position for the scara rrpr manipulator, yielding a transformation with x4 parallel to x0, y4 opposite y0, and z4 opposite z0.
Analyze the home position of a scara (rrpr) manipulator using the modified dh convention, deriving the end-effector position from base to frame five and verifying the home transformation matrix.
Determine the home position of the cylindrical manipulator using the modified dh convention by setting theta1 to zero and deriving the end effector location at x0, y d3, z d2.
Explore modified DH parameters for a Cartesian manipulator with three perpendicular prismatic joints, assign frames, and derive the transformation matrices to obtain the frame three with respect to the base.
This comprehensive course on Robotics: Fundamentals and Kinematic Modeling (Part 1) is designed to provide students with a thorough understanding of the basic principles and mathematical modeling techniques fundamental to robotic manipulators. The course begins by introducing the core concepts of robotics, distinguishing between robots and manipulators, and exploring various robot configurations to highlight the diversity in robotic system design. It covers the types of joints used in manipulators, differentiating between active and passive joints, and explains key terminologies that define a robot’s capabilities, limitations, and task suitability. Students also learn about essential components such as stepper and servo motors, along with their feedback devices, critical for robot motion control.
The curriculum then shifts focus to end effectors, discussing different types of grippers and the basics of robot programming, which lay the groundwork for robot operation and task execution. A significant emphasis is placed on transformation and orientation, where students study the need for matrix transformations in robotic manipulators. Topics include Euler angles, their role and singularities, and homogeneous transformations vital for describing robot motion and positioning in space.
A key focus of the course is an in-depth exploration of Denavit–Hartenberg (DH) parameters, including both classical and modified conventions, which are widely used in forward kinematics to describe the geometric structure of robot manipulators. Students will learn systematic procedures for assigning coordinate frames and determining DH parameters in a clear and structured manner.
The course incorporates hands-on examples involving a variety of manipulators such as SCARA, spherical, articulated, cylindrical, and Cartesian configurations. Learners will also study how to determine home positions and develop transformation sequences, enabling accurate spatial representation and analysis of robotic links and joints.
By integrating theory with practical applications, this course equips learners with the essential skills to model robotic manipulators mathematically, understand their kinematic behavior, and prepare for more advanced topics such as robot dynamics, control, and motion planning. It is ideal for engineering students, researchers, and professionals aiming to build a strong foundation in robotics. To strengthen practical and technical understanding, the course also includes interactive role-play exercises.