Abstract
Abstract. Redundant manipulators (RMs) have been gaining more attention thanks to their excellent merits of operating flexibility and precision. Inverse kinematics (IK) study is critical to the design, trajectory planning, and control of RMs, while it is usually more complicated to solve IK problems which may inherently have innumerable solutions. In this work, a novel approach for solving the IK problems for RMs while retaining the redundancy characteristics has been proposed. By employing a constraint function, the method delicately reduces the infinite IK solutions of a RM to a finite set. Furthermore, the workspace of RMs is divided into nonlinear partitions through diverse joint angle intervals, which have further simplified the mapping correlations between the desired point and manipulators' joint angles. For each partition, a pre-trained neural network (NN) model is established to acquire its IK solutions with high efficiency and precision. After combing all nonlinear partitions, multiple reasonable IK solutions are available. The presented method offers a possible selection of the most appropriate solution for trajectory planning and energy consumption and therefore has the potential for facilitating novel robot development.
Highlights
Redundant manipulators (RMs) have been widely used in many fields, such as industrial and agricultural production, equipment manufacturing, and surgical operation
The nonlinear workspace of a RM was divided into several parts which were correspondingly fitted by a neural network model
We find that different joint angle combinations may result in various inverse kinematics (IK) solutions
Summary
Redundant manipulators (RMs) have been widely used in many fields, such as industrial and agricultural production, equipment manufacturing, and surgical operation. RMs can move freely in joint space without affecting the position and pose of the end effector. Once the pose of an end effector is defined, the secondary target can be satisfied by changing joints’ positions. Control of a manipulator requires computationally efficient solutions of the inverse kinematics (IK) problem, while for a desired position and orientation, combinations of joint variables of a RM may be infinite. This issue is caused by two things: (a) deficient definition for joint angles; (b) symmetry of trigonometric functions. The IK issues of RMs are often too complicated to be solved, especially for the complex systems meeting real time and high precision
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