Based on a heuristic optimization algorithm, this paper proposes a new algorithm named trajectory-planning beetle swarm optimization (TPBSO) algorithm for solving trajectory planning of robots, especially robot manipulators. Firstly, two specific manipulator trajectory planning problems are presented as the practical application of the algorithm, which are point-to-point planning and fixed-geometric-path planning. Then, in order to verify the effectiveness of the algorithm, this paper develops a control model and conducts numerical experiments on two planning tasks. Moreover, it compares with existing algorithms to show the superiority of our proposed algorithm. Finally, the results of numerical comparisons show that algorithm has a relatively faster computational speed and better control performance without increasing computational complexity.

Introduction

The robotic arm, or the manipulator, has similar functions to a human arm and can be either a separate mechanism or part of a more complex robot [1]. It can be considered that the link of the robot arm forms a kinematic chain, and the end of the kinematic chain is called an end-effector for performing actual operations such as grasping, spraying, cutting, etc. The robotic arm is widely used in modern society. In the field of industrial manufacturing, it is used for assembly, spraying, welding etc [2]. In the medical field, it is used as a surgical aid [3], [4]. And in agriculture, for picking vegetables and fruits. Even in space exploration the robotic arm can also find its application. In the research area of robot manipulator, trajectory planning has always been a hot spot, which is usually performed with constraints that may come from dynamic equations or from the inputs [5]. There are several important issues in the study of manipulator trajectory planning, one of which is the solution of inverse kinematics transformation [6]–[۱۰]. Due to the high nonlinearity of inverse kinematics transformation, the solution process is difficult. Therefore, improving the efficiency and effectiveness of inverse kinematics is very important in manipulator trajectory planning, especially in redundant manipulator trajectory planning [11]–[۱۸]. The second is obstacle avoidance. In many manufacturing applications today, robot manipulators must use their endeffector to pass through the desired curve while their fuselage avoids collisions with obstacles in the environment.