As a result, it is preferable to solve the IK of the complex manipulator using a metaheuristic approach 9. Still, it is difficult to obtain satisfactory solutions by traditional methods, and the real-time performance is poor. The IK of redundant manipulators may have many group solutions.
The gunk all upgrades serial#
However, with the increase of the types of manipulators, many manipulators do not meet the Pieper standard, such as serial-parallel manipulators driven by cable 7 and super-redundant serial manipulators 8. The IK problem has an analytical solution for a manipulator that conforms to the Pieper standard. The traditional methods for solving inverse kinematics mainly include the analytic method and numerical iteration method 5, 6. However, the IK of redundant manipulators is a complex problem due to nonlinear Equations 4. It is one of the most fundamental problems in robot technology and plays an essential role in robot motion control, trajectory planning, and dynamic analysis 3. That is, the purpose is to accurately transfer the end-effector to the desired position and posture 2. The inverse kinematics (IK) problem is to determine the joint angle based on the position and posture of the manipulator's end-effector 1. In two scenarios, the average convergence accuracy of EOSMA is 10e−17 and 10e−18, and the average solution time is 0.05 s and 0.36 s, respectively. The results show that EOSMA has higher accuracy and shorter computation time than previous studies. Then, EOSMA and MOEOSMA are applied to the IK of the 7 degrees of freedom manipulator in two scenarios and compared with 15 single-objective and 9 multi-objective algorithms. On this basis, a multi-objective EOSMA (MOEOSMA) is proposed. Finally, the random difference mutation operator is added to EOSMA to increase the probability of escaping from the local optimum.
The gunk all upgrades update#
Then, the greedy strategy is used to update the individual and global historical optimal to accelerate the algorithm’s convergence. Firstly, the concentration update operator of the equilibrium optimizer is used to guide the anisotropic search of the slime mould algorithm to improve the search efficiency. In order to solve the inverse kinematics (IK) of complex manipulators efficiently, a hybrid equilibrium optimizer slime mould algorithm (EOSMA) is proposed.
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