Inverse Kinematics of 2 and 3 DOF Robots Explained

Added:

Recap & Fix
2-DOF IK Solution
3-DOF Setup
Solving Theta3
Solving Theta2
FK & Plotting
Summary & Next

Recap & Fix

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Playing Section
  • 1

    Reviewing previous inverse kinematics concepts for 2-DOF robots.

  • 2

    Addressing numerical issues with pi using symbolic evaluation.

Fundamental trigonometry, including the Law of Cosines, Pythagorean theorem, and the atan2 function.
Basic vector mathematics and coordinate transformations in 2D and 3D Cartesian space.
The concept of Forward Kinematics (calculating end-effector position from given joint angles).
Understanding robotic joint types (revolute and prismatic) and Degrees of Freedom (DOF).
Differential Kinematics and the Jacobian matrix for velocity analysis and singularity detection.
Numerical Inverse Kinematics methods (e.g., Newton-Raphson, Levenberg-Marquardt) for redundant or high-DOF robots (6+ DOF).
Systematic frame formulation using the Denavit-Hartenberg (DH) convention for complex serial manipulators.
Trajectory planning algorithms to interpolate smooth paths between calculated inverse kinematics joint states.
2.4K views32likes15:28@eliasbrassitos1Original Release: 2020-10-16

Inverse kinematics determines joint angles (θ₁, θ₂, θ₃) from end-effector Cartesian coordinates (X, Y, Z) for robots with rotational joints; for 2-DOF robots, solve θ₂ using the law of cosines (cos(θ₂) = (L² - L₁² - L₂²)/(2L₁L₂)) where L = √(XE² + YE²), then find θ₁ using arctan2 with α = arctan2(L₂sin(θ₂), L₁ + L₂cos(θ₂)) and β = arctan2(YE, XE); for 3-DOF robots, first solve θ₁ = arctan2(YC, XC), then compute θ₃ using the same law of cosines with modified virtual link L' = √(XC² + YC² + (ZC-L₁)²), and finally solve θ₂ using θ₂ = β - α where α = arctan2(L₃sin(θ₃), L₂ + L₃cos(θ₃)) and β = arctan2((ZC-L₁), √(XC² + YC²)), with homogeneous transformations enabling visualization and animation of the robot's motion.