Inverse Kinematics For Serial Robot Manipulator End Effector Position And Orientation By Particle Swarm Optimization

L. Nguyen, Hasan Danaci, T. L. Harman
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Abstract

This paper investigates the use of Particle Swarm Optimization (PSO) approach in solving the inverse kinematics problem for serial robotic manipulators. 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 reviewed robotic manipulator inverse kinematics solutions using swarm intelligence only deal with end effector position and not its orientation. Our PSO approach provides the convergence of a complete end effector pose and 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.
基于粒子群优化的串联机器人末端执行器位置和姿态逆运动学
研究了用粒子群算法求解串联机器人的运动学逆问题。逆运动学是机器人技术中的一个基本问题:必须计算一组关节角,以便机器人手臂可以被操纵到相应的期望末端执行器的位置和方向。传统的求解技术包括对特定机器人可能存在或不存在的解析方法,数值方法如牛顿-拉夫森,雅可比逆和其他使用群体智能的技术已经发展起来。目前已有的机器人逆运动学求解方法中,多数只考虑末端执行器的位置,而不考虑末端执行器的方向。我们的PSO方法提供了一个完整的末端执行器姿态的收敛性,并将使用Baxter研究机器人进行演示,该机器人具有两个七关节手臂,尽管该方法可以应用于任何一般的串行机器人机械手。
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