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In this study, a novel parallel learning particle swarm optimizer (PLPSO) is proposed. The evolutionary strategy of the algorithm is quite different from that of the existing PSO algorithms. To enhance the global search capability of the particle swarm, the original particle swarm is divided into two parallel evolving independent particle subpopulations to explore the search space simultaneously. In addition, according to the evolutionary factor in each iteration, the poorly performing particles in the two subpopulations are spurred and learned to improve the search speed of the particle swarm. In the process of particle learning, delay information is added to the velocity update item to reduce the occurrence of local capture. Twenty-eight benchmark functions of CEC2013 are used to evaluate the performance of the proposed PLPSO algorithm. Numerous comparisons demonstrate that the performance of the PLPSO algorithm is better than that of other nine PSO algorithms. Afterwards, the PLPSO algorithm is applied to the inverse kinematics (IK) solution of a robotic manipulator. By comparing with other three intelligent algorithms, the PLPSO algorithm shows an excellent performance in solving the IK problem. Finally, tests are carried out on an UR5 manipulator to confirm the practicability of the proposed PLPSO algorithm further. Thus, the feasibility of using the PLPSO algorithm for solving the IK problem of a robotic manipulator is verified.

Investigated in this paper is the effect of nongeometric errors on manipulator inertial calibration. Nongeometric errors are referred to as joint friction, backlash and compliance. To account for this effect, the total least square (TLS) method and the instrumental variable (IV) method are applied to determine the estimates of the link inertial parameters. Results of simulation show that the TLS and IV methods can improve the accuracy of manipulator inertial calibration when subjected to nongeometric errors.

Point-to-point quasi-static motion planning is essential for effectively controlling the elastic deformations and vibrations of the end-effector of flexible-link manipulators. In this paper, this problem is formulated considering the kinematic equations and link deflection equations of the manipulator. An algorithm is proposed to obtain the numerical solution to the problem by utilizing the Newton-Raphson method. The kinematic equations and link deflection equations, as well as their differential relationships, are derived by using the algebra of rotations. The effectiveness of the proposed algorithm is demonstrated in examples.>

A spacecraft-manipulator system is considered in this paper. Dynamic singularities are the singularities occurring when inverting the system generalized Jacobian required by the conventional method for solving the inverse kinematics of space manipulators. To avoid dynamic singularities three methods are developed here based on the manipulator Jacobian, instead of the system generalized Jacobian. These methods are compared with the conventional method on the basis of their convergence rate, accuracy and sensitivity. Results of this comparison are presented in this paper.>

The basic quantities required for computations in robot kinematics, dynamics, and control are defined. By modifying the rotational operator in terms of the Euler parameters and appropriately choosing the zero reference position, the method of the algebra of rotations becomes more efficient than the homogeneous transformation method for computing these basic quantities. As a result, the computational efficiency is improved by about 50|% for robot kinematics, and by about 20|% for robot dynamics and control, if the method of the algebra of rotations is used instead of the homogeneous transformation method.>

In this paper, a complete model of the elasto-kinematics is formulated in terms of a new kinematic notation, called the algebra of rotations. Based on this formulation, the elegant and concise expressions are derived for the displacement equation and especially the Jacobians governing the motion mapping between the manipulator tip and joint variables and link deflections. Introduction of the elasto-kinematics into the elasto-dynamics can directly take into consideration the nonlinear coupling between joint variables and link deflections, and thus improve the result of the elasto-dynamics.>

An algorithm for motion planning of flexible manipulators in quasi-static operations is proposed. This method is based on the algebra of rotations. A concise motion expression for flexible manipulators is developed to reflect the contributions of joint motions and link deflections to the motion of the end effector by three respective Jacobians. The proposed algorithm is composed of two major loops: the first for joint motions and the second for link deflections. The problems associated with the implementation of the algorithm are investigated, including convergency analysis, singularity analysis, link deflection analysis, etc. It is found that the algorithm is efficient and accurate for motion planning of flexible link manipulators.>