Abstract
Although the solution of inverse kinematics for a serial redundant manipulator has been widely researched, many algorithms still seem limited in dealing with complex geometries, including multi-finger anthropomorphic hands. In this paper, the inverse kinematic problems of multiple fingers are an aggregate problem when the target points of fingers are given. The fingers are concatenated to the same wrist and the objective is to find a solution for the wrist and two fingers simultaneously. To achieve this goal, a modified immigration genetic algorithm based on workspace analysis is developed and validated. To reduce unnecessary computation of the immigration genetic algorithm, which arises from an inappropriate inverse kinematic request, a database of the two fingers’ workspace is generated using the Monte Carlo method to examine the feasibility of inverse kinematic request. Furthermore, the estimation algorithm provides an optimal set of wrist angles for the immigration genetic algorithm to complete the remaining computation. The results reveal that the algorithm can be terminated immediately even when the inverse kinematic request is out of the workspace. In addition, a distribution of population in each generation illustrates that the optimized wrist angles provide a better initial condition, which significantly improves the convergence of the immigration genetic algorithm.
Highlights
A workspace-analysis-based immigration genetic algorithm was presented to solve the inverse kinematics of a multi-fingered hand
An estimation function is used to check the feasibility of the target point whenever an inverse kinematics (IK) request is assigned
If the target point is within the workspace, the estimation function provides an optimal set of wrist angles for the immigration genetic algorithm (IGA) to compute the solution; contrarily, the estimation function terminates further calculation
Summary
The IK of a manipulator is used to find the map between the joint coordinate (θ) and the Cartesian coordinates (x, y, z), where θ represents the joint angles of each joint in the manipulator and (x, y, z) represent the position of the manipulator’s end-effector. In addition to the basic accurate positioning, different requirements such as computation time, robustness, and minimum displacement are considered suboptimal conditions. One of these complex redundant manipulators is the multi-fingered anthropomorphic robotic hand, whose joints of fingers move simultaneously and two wrist joints are deemed as the base of the hand. To obtain the IK solution of the anthropomorphic hand, a robust algorithm is essential to solve this multiple end-effector problem
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