Abstract
Inverse kinematic solutions for a dual redundant camera robot in position are examined in order to alleviate operation difficulty and reduce time. The inverse kinematic algorithm is based on a basic genetic algorithm, and the genetic algorithm which is used to solve the problem of a redundant robot is mainly optimized in the joint space. On this basis, the genetic algorithm improvement strategies are studied. In this paper, a genetic algorithm with constrained 2 redundant degrees of freedom (DOF) is proposed through setting 2 parameter variables, with more flexible structure of optimization objective function and more efficient algorithm than basic genetic algorithm. Finally, the result of inverse kinematic algorithm is achieved in terms of the physical prototype.
Highlights
Coupled with mechanism geometric flexibility, a robot intelligent control system serves to complete a variety of complex operational tasks [1]
The inverse kinematic solutions for a redundant robot are expressed as solutions of nonlinear equations, which generally can only be solved based on numerical iterative methods
The inverse kinematic solutions of camera robot are obtained by genetic algorithm, which takes an arbitrary set of 2dimensional vector of 2 redundant degrees of freedom (DOF) as an individual in physical constraint
Summary
Coupled with mechanism geometric flexibility, a robot intelligent control system serves to complete a variety of complex operational tasks [1]. Optimization objective function, sometimes called fitness function, consists of the minimum position error and rotation angle of each joint and solves to inverse kinematics in accordance with explicit expression from transformation matrix of a redundant robot [18]. Make CRCP camera robot current position zero point; paT is homogeneous matrix of target position In terms of this algorithm, the basic genetic algorithm parameters are set in the joint space, and an experiment is simulated by MATLAB. The inverse kinematic solutions based on basic implicit genetic algorithm with constrained 2 redundant DOF are proposed to replace explicit expression of fitness function on individual genes. The inverse kinematic solutions of camera robot are obtained by genetic algorithm, which takes an arbitrary set of 2dimensional vector of 2 redundant DOF as an individual in physical constraint. It is due to the fact that the range of bottom and top linear motion is larger, and the possibility of obtaining effective solution from random values in 2 redundant DOF is quite low
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