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DTSTAMP:20230713T151407Z
UID:057F1990-0FDB-4FAE-A6BE-135020ED378A
DTSTART;TZID=America/Chicago:20230708T113000
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DESCRIPTION:Inverse kinematics is a fundamental problem in manipulator robo
 tics: a set of joint angles must be calculated so that the robot arm can b
 e manipulated to the corresponding desired end effector position and orien
 tation (also known as "pose"). Traditional solution techniques include ana
 lytical kinematics solvers which provide the closed-form expressions for t
 he joint positions as functions of the end effector pose. When analytical 
 inverse kinematics solvers are not possible due to the manipulator structu
 re\, numerical methods such as Newton-Ralphson or Jacobian inverse can be 
 used to achieve the task but at a much slower speed due to the iterative n
 ature of the computation. Recent swarm intelligence technology has also co
 ntributed to manipulator inverse kinematics solutions. In this presentatio
 n\, we investigate the use of the Particle Swarm Optimization (PSO) approa
 ch in solving the inverse kinematics problem for the general serial roboti
 c manipulators. Many of the reviewed robotic manipulator inverse kinematic
 s solvers using swarm intelligence only deal with the end effector positio
 n and not its orientation. Our PSO approach provides the convergence of a 
 complete end-effector pose and will be demonstrated using the Baxter Resea
 rch Robot which has two seven-joint arms although the method is applicable
  to any general serial robotic manipulator.\n\nSpeaker(s): \, HASAN\n\nHou
 ston\, Texas\, United States
LOCATION:Houston\, Texas\, United States
ORGANIZER:ztaqvi@gmail.com
SEQUENCE:16
SUMMARY:Webinar:"Application of Particle Swarm Optimization in Robot Manipu
 lator Inverse Kinematics with POSIX Threads Implementation”
URL;VALUE=URI:https://events.vtools.ieee.org/m/365785
X-ALT-DESC:Description: <br /><p>&nbsp\;Inverse kinematics is a fundamental
  problem in manipulator 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 (also known as "pose"). Traditional sol
 ution techniques include analytical kinematics solvers which provide the c
 losed-form expressions for the joint positions as functions of the end eff
 ector pose. When analytical inverse kinematics solvers are not possible du
 e to the manipulator structure\, numerical methods such as Newton-Ralphson
  or Jacobian inverse can be used to achieve the task but at a much slower 
 speed due to the iterative nature of the computation. Recent swarm intelli
 gence technology has also contributed to manipulator inverse kinematics so
 lutions. In this presentation\, we investigate the use of the Particle Swa
 rm Optimization (PSO) approach in solving the inverse kinematics problem f
 or the general serial robotic manipulators. Many of the reviewed robotic m
 anipulator inverse kinematics solvers using swarm intelligence only deal w
 ith the end effector position and not its orientation. Our PSO approach pr
 ovides the convergence of a complete end-effector pose and will be demonst
 rated using the Baxter Research Robot which has two seven-joint arms altho
 ugh the method is applicable to any general serial robotic manipulator.&nb
 sp\;</p>
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