Particle Swarm Optimization (PSO) is one of the most popular Swarm Intelligence paradigms and is a population-based stochastic algorithm that can be used to solve many types of optimization problems in engineering. This presentation will show how to solve the inverse kinematics problem for serial robotic manipulators using PSO. Inverse kinematics is a fundamental problem in robotics: a set of joint angles must be calculated so that the robot arm can be manipulated to the corresponding desired end effector position and orientation. Traditional solution techniques include analytical methods which may or may not exist for a particular robot, numerical methods such as Newton-Raphson, Jacobian inverse, and other techniques using swarm intelligence have been developed. Many of the current robotic manipulator inverse kinematics solutions using swarm intelligence only deal with the end effector position and not its orientation. We have developed a PSO technique that provides the convergence of a complete end effector pose. This solution technique will be demonstrated using the Baxter Research Robot which has two seven-joint arms although the method can be applied to any general serial robotic manipulator. Speaker(s): HASAN, Virtual: https://events.vtools.ieee.org/m/320721