
Define robot geometry and joint trajectories, build homogeneous transformation matrices using classical denavit-hartenberg or modified denavit-hartenberg conventions, and compute forward kinematics to simulate and visualize the end-effector pose in MATLAB.
Apply the classical denavit-hartenberg convention with theta, d, a, alpha to build the four-parameter transformation from frame i-1 to i for MATLAB-based robotics simulations.
Explain the modified Denavit-Hartenberg convention using alpha i-1, a i-1, theta i, and d i to form a 4x4 homogeneous transformation matrix from frame i-1 to i, via rotation-translation-rotation-translation.
Simulate a three-link planar manipulator in MATLAB by applying forward kinematics to compute joint positions, plot links, and animate forward and backward trajectories with end-effector tracking.
Explore a MATLAB simulation of a 3-link RRR planar manipulator, viewing an alternative 3D view and tracking the end effector as it moves forward and backward.
Visualize a 3-link planar manipulator in MATLAB with a 3D view, labeling links, joints, and frames, and track the end effector path and joint angles Q1, Q2, Q3.
Explore 2D view of a three-link planar RRR manipulator in MATLAB, observe forward and backward motion, and track end-effector x and y coordinates (z is zero) as it returns home.
Explore the MATLAB simulation of a prismatic joint moving from 0.2 to 0.8 meters, with a home position at 0.5 meters and 0.3 meter amplitude, showing forward and backward motion.
Apply Denavit-Hartenberg parameters to a four-joint SCARA manipulator with three revolute and one prismatic joint, and implement forward kinematics in MATLAB to relate the base frame to the end effector.
Explore MATLAB-based forward kinematics and visualization of a SCARA RRPR manipulator using classical DH convention, with 3d and z-projection plots and animated trajectories.
Demonstrates a scara rrpr manipulator simulated under the classical dh convention, showing 3d and z-projection views, joint trajectories, and end-effector position in world coordinates.
learn to model a four-joint scara arm (three revolute, one prismatic) with the modified dh convention, allocate frames, and derive the dh parameters and end-effector pose in matlab.
Simulate a SCARA rrpr manipulator in MATLAB using the MDH convention, visualizing a 3D view and a z projection with forward and reverse joint trajectories and end-effector path.
Simulate a scara rrpr robotic arm with the modified dh convention, revealing forward kinematics and end-effector motion through 3d and xz projections.
Explore the modified Denavit-Hartenberg convention for a scara arm with three revolute and one prismatic joints, deriving forward kinematics and end-effector pose using Matlab simulations and frame assignments.
Demonstrate a SCARA RRPR type manipulator in MATLAB using the modified DH convention, setting link lengths and base height, and animating 3D and z projection trajectories via sinusoidal joint motions.
Explore a Scara (rrpr) robot arm simulation in MATLAB using the modified DH convention, visualizing end-effector position in 3d and z projection with joints theta1, theta2, d3, and theta4.
Model a three-revolute robotic arm using classical denavit-hartenberg convention in MATLAB. Analyze frame placement and forward kinematics to obtain the end-effector pose via transformation matrices T1, T2, T3.
Explore a three-revolute rrr manipulator in matlab using the classical dh convention, initializing d1, l2, l3, and simulating forward kinematics with 3d and projection views.
Demonstrates an articulated RR robotic arm using the classical DH convention, with 3D visualization, z and y projections, labeled joints, and end-effector path tracking.
Model a three-revolute manipulator with the modified Hardenbergh parameters and DH convention in Matlab, assigning frames at joint axes and deriving the end-effector pose relative to the base.
Demonstrate simulating a rrr manipulator in Matlab using the modified inverse hartenberg convention. Initialize robot parameters, joint limits, and trajectories, then animate the end effector with 3d views and projections.
Simulate a triple rrr manipulator with the modified dh convention in matlab, label joints j1–j3, and track end effector path in 3d view, with z and y projections toward home.
Apply classical Denavit-Hartenberg parameters in MATLAB to model an RRP manipulator with two revolute joints and one prismatic joint, locate frames, and compute forward kinematics.
Explore a MATLAB script that simulates an RRP manipulator with the classical DH convention, computing transformation matrices, plotting 3D and z projection views, and animating forward and reverse joint trajectories.
Simulate a classical DH RRP manipulator in MATLAB, with theta1, theta2 and d3, moving from home, tracking end effector in 3d and z-x projections, then returning to home.
Model a two-revolute plus one prismatic spherical arm using the modified DH convention in MATLAB, deriving frame locations, MDH parameters, and transformation matrices for end-effector positioning.
analyze a Matlab script for a spherical rp manipulator using the modified dh convention, visualizing 3d view, z-projection trajectories, and forward kinematics of the end effector.
Explore forward and backward motion of a spherical robotic arm using the modified DH convention, with revolute and prismatic joints, and track end-effector position in world coordinates.
Learn classical denavit-hartenberg modeling for a cylindrical robot arm with one revolute and two prismatic joints using MATLAB, focusing on frame placement and forward kinematics.
Explore a MATLAB script for an RPP cylindrical manipulator using classical DH convention to initialize parameters, compute forward kinematics, generate joint trajectories, and visualize 3d and xz end-effector projections.
See a 3d simulation of a cylindrical rrp manipulator using classical dh convention, with one revolute and two prismatic joints, tracking end-effector positions in x, y, and z.
demonstrates modeling a cylindrical rpp manipulator using modified dh parameters in MATLAB, deriving forward kinematics and transformation matrices to compute the end-effector position and orientation.
Simulate a cylindrical RPG type manipulator in MATLAB using the modified DH convention to analyze forward kinematics and end-effector motion in 3D view and z projection.
Simulate a cylindrical RPP manipulator in 3d using a modified dh convention, visualizing the end effector path, local versus world coordinates, and the forward and return motion with z projections.
Model a triple prismatic joint Cartesian manipulator using the classical DH convention in Matlab, locating frames, defining theta, d, a, alpha, and deriving transformation matrices to compute end-effector pose.
Simulate a cartesian triple prismatic manipulator in matlab using the classical denavit-hartenberg convention to plot transformation matrices and the end-effector trajectory in a 3d view.
Visualizes a 3d simulation of a cartesian triple prismatic manipulator with perpendicular axes, showing d1, d2, d3 motion, base pedestal distance 0.1 m, and tracking the end effector.
Explore the modified Denavit-Hartenberg modeling of a Cartesian triple prismatic manipulator in MATLAB, deriving frame assignments, DH parameters, and transformation matrices to determine the end-effector pose.
Demonstrate a MATLAB script for a Cartesian triple prismatic manipulator using the modified DH convention. Compute end-effector position and orientation via transformation matrices with 50-step forward and return trajectories.
Explore a 3d Cartesian manipulator with a modified dh convention, showing forward and return motions driven by three prismatic joints along z1, z2, and z3, and end effector tracking.
Explore inverse kinematics for a two-link planar robot, analyzing elbow up and elbow down configurations with MATLAB simulations, deriving theta1 and theta2 from end-effector pose.
Explore inverse kinematics for a two-link planar robot in MATLAB, computing q1 and q2 for elbow up or elbow down, checking reachability and animating trajectories.
Demonstrate inverse kinematics for a two-link planar arm using elbow up and elbow down, showing how q2 signs drive motion toward the target at (2.5, 1.5) with both configurations.
Analyze elbow up and elbow down validity in a two-link planar robot using MATLAB scripts, inverse kinematics, joint limits, and trajectory planning to reach a target end effector.
Show elbow up as the valid configuration in the MATLAB simulation (solid blue line) and elbow down as invalid (dashed red line) for the distal end of link two.
Explore inverse kinematics for a 3R planar manipulator, comparing elbow up and elbow down configurations to reach the target in x and y.
Analyze the rope manipulator's three degree of freedom simulation with local coordinate frames and explore end effector positions along x, y, and z in global coordinates using inverse kinematics.
Visualize a robotic manipulator in MATLAB using inverse kinematics to reach a target position along x, y, and z directions, calculating joint variables and analyzing z and y axis projections.
Derive the three-revolute planar manipulator dynamics using the Euler-Lagrange method, forming the inertia matrix M(q), the Crowley's and centrifugal forces matrix C(q,qdot), and gravity vector G(q) to compute joint torques.
Simulate a three-DOF planar rr manipulator in Matlab, deriving Euler-Lagrange dynamics to compute inertia, gravity vector, centrifugal terms, and the resulting joint torques using symbolic q1–q3.
Analyze the dynamic simulation of a three-degree-of-freedom RRP manipulator using jacobian-based velocity calculations, kinetic and potential energies, and the Euler-Lagrange equations to compute joint torques and prismatic force.
Analyze how vertical and horizontal prismatic motion alters the inertia matrix in an RRP manipulator, and compute torques and prismatic forces via the two-language method using MATLAB.
Implement a MATLAB script for an rb manipulator with two revolute joints and one vertical prismatic joint, deriving inertia, centrifugal, and gravity terms and computing torques and force.
Apply the Euler–Lagrange framework in MATLAB to an RRP manipulator with a horizontal prismatic joint, deriving the inertia, Coriolis, and gravity terms to compute joint torques and prismatic force.
Apply Euler-Lagrange dynamics to the ARP manipulator to study torques for two revolute joints and the prismatic force over time, using a MATLAB script that plots these values.
Analyze how the torques at the first and second joints and the prismatic joint force F3 vary with time in this rope manipulator, using the simulation results.
Explore MATLAB-based robotic trajectory profiles, from linear to quintic, including trapezoidal and s-curve paths, with time-based position, velocity, and acceleration for smooth end-effector motion.
Explore MATLAB scripts for a 3-link planar robot to compare linear, cubic, quintic, trapezoidal, and S-curve trajectories, analyze fastest arrival times, and visualize with forward kinematics.
Analyze a three-link planar manipulator with Q1, Q2, Q3. Five trajectories, including quintic and S-curve, yield minimum arrival times and fastest forward motion back to the zero-degree home position.
The course " Robotics: Kinematics & Dynamics Simulation in MATLAB (Part3)" bridges theory and application by combining Denavit–Hartenberg (DH) modeling, kinematic analysis, and dynamic simulation through MATLAB programming. You will learn how to design and analyze robotic manipulators such as SCARA, RRP (Spherical) , RPP (Cylindrical), RRR (Articulated) , and PPP (Cartesian) arms; visualize their motion in both 2D and 3D, and understand how their physical structure influences workspace and performance.
Starting with the fundamentals of Classical and Modified Denavit–Hartenberg (DH) conventions, you’ll learn to construct transformation matrices, derive forward and inverse kinematics, and explore the geometric interpretation of elbow-up and elbow-down configurations in 2-link planar robots. This provides a clear understanding of how multiple joint combinations can achieve the same end-effector position, and when each configuration is most suitable in industrial or academic contexts.
Moving beyond kinematics, the course delves into robot dynamics using the Euler–Lagrange formulation. You will derive and implement the Inertia (M), Coriolis/Centrifugal (C), and Gravity (G) matrices, and learn how these affect manipulator motion and control. With complete MATLAB coding demonstrations, you’ll generate end-effector trajectories, visualize workspace coverage, and animate manipulator motion step-by-step. Additionally, Geometric Modeling of Robotic Arms and their animation in MATLAB also performs in simple manner
By the end of this course, you will be able to:
Develop kinematic and dynamic models of robotic manipulators
Apply Classical Denavit–Hartenberg and Modified Denavit–Hartenberg conventions for serial link robots
Simulate 3D motions and 2D projections (XY, XZ, or YZ views) using MATLAB visualization tools
Derive and implement forward and inverse kinematics (including elbow-up and elbow-down such as for 2R and 3R planar manipulator arms)
Construct Euler–Lagrange dynamic equations for manipulators like RRR and RRP
Analyze Coriolis, centrifugal, and gravitational effects on motion
Generate and interpret end-effector trajectories and workspace plots
This course is ideal for:
Students and researchers in Mechanical, Mechatronics, Robotics, or Electrical Engineering
Professionals and enthusiasts looking to strengthen skills in robot modeling, kinematics, and dynamics
Automation and control engineers, software developers, and hobbyists working with MATLAB or robotic manipulators
Participants preparing for robotics projects, simulations, or competitions