Trajectory planning of redundant manipulator using fuzzy clustering method

Abstract

The solution of inverse kinematics and trajectory planning with performance criteria for a redundant manipulator is proposed with modification in fuzzy c-means. A new fuzzy clustering model based on a new generalized validity index based on weighted within-scatter metrics and betweencluster scatter metrics for the manipulator is proposed. In order to understand the proposed algorithm and to show its performance, two simulation studies of trajectory planning with manipulability criteria for a redundant manipulator are modeled to solve the problems of finding association rules in the data and of setting up an appropriate classification procedures. The problem of redundant manipulator (which is a multi-input, multi-output nonlinear system) is new in terms of solution by clustering method. The proposed algorithm for the trajectory planning of the manipulator is simulated using Matlab®. All practical steps, from data acquisition to model validation, are illustrated using a 4 degree of freedom robot manipulator. The simulated results are compared with the numerical methods of the trajectory planning. The results are presented graphically. The proposed method has the advantage of simplicity, flexibility, and good tracking performance.

Predicting the Motion of a Robot Manipulator with Unknown Trajectories Based on an Artificial Neural Network

“…Robot manipulators are governed by two basic kinematic theories, namely forward kinematics (FK) and inverse kinematics (IK). FK theory calculates the position and orientation of the hand or wrist (end effector) base on the robot's configuration, and the robot's configuration is assumed to be known in terms of all the joint variable angles and the length of links [10,16,17,21,23,34]. Conversely, given the desired position and the orientation of the end effector ( ) t r E , IK theory enables the robot to calculate all the joints values θ, to place itself at the desired location and orientation [10,16,17,21,23,[26][27]29,35].…”

“…Basically, there are two types of motion planning for a robot, namely path planning [14][15][16][17] and trajectory planning [7][8][9][12][13][14][18][19][20][21][22]. However, trajectory planning will be more practical compared to path planning as it includes the motion timing, velocities and accelerations.…”

“…Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics (forward and inverse kinematics), dynamics and trajectory-planning calculations [1–22]. However, it is difficult to apply these mathematical solutions.…”

Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems

“…Modeling kinematics and dynamic constraints without a loss of transparency and accuracy in master-slave surgical robots remains a challenging task and it has attracted research interests in recent years [6,11,12]. In general, kinematics resolutions basically involve defining apt relationships between the joint and Cartesian spaces of a robot.…”

Estimation of stochastic environment force for master–slave robotic system

“…are the subject of present research and researchers have suggested various control techniques to tackle some of these problems. Model prediction adaptive controller [3], robust lsynthesis controllers [4,5], intelligent controllers [6][7][8], nonlinear and composite adaptive controller [7,9] and disturbance observer [10] have been used to control such dynamical systems. Further, the environment, operator and task (EOT) adaptive controllers have been considered in [11] highlighting the importance of on-line information for the control.…”