scholarly journals New insights into input relegation control for inverse kinematics of a redundant manipulator. Part 2, The optimization of a secondary criteria involving self motion of the joints

10.2172/89523 ◽  
1995 ◽  
Author(s):  
M.A. Unseren
Robotica ◽  
2015 ◽  
Vol 34 (12) ◽  
pp. 2669-2688 ◽  
Author(s):  
Wenfu Xu ◽  
Lei Yan ◽  
Zonggao Mu ◽  
Zhiying Wang

SUMMARYAn S-R-S (Spherical-Revolute-Spherical) redundant manipulator is similar to a human arm and is often used to perform dexterous tasks. To solve the inverse kinematics analytically, the arm-angle was usually used to parameterise the self-motion. However, the previous studies have had shortcomings; some methods cannot avoid algorithm singularity and some are unsuitable for configuration control because they use a temporary reference plane. In this paper, we propose a method of analytical inverse kinematics resolution based on dual arm-angle parameterisation. By making use of two orthogonal vectors to define two absolute reference planes, we obtain two arm angles that satisfy a specific condition. The algorithm singularity problem is avoided because there is always at least one arm angle to represent the redundancy. The dual arm angle method overcomes the shortcomings of traditional methods and retains the advantages of the arm angle. Another contribution of this paper is the derivation of the absolute reference attitude matrix, which is the key to the resolution of analytical inverse kinematics but has not been previously addressed. The simulation results for typical cases that include the algorithm singularity condition verified our method.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 18662-18674 ◽  
Author(s):  
Mingde Gong ◽  
Xiangdong Li ◽  
Lei Zhang

Author(s):  
B. Moore ◽  
E. Oztop

Our overall research interest is in synthesizing human like reaching and grasping using anthropomorphic robot hand-arm systems, as well as understanding the principles underlying human control of these actions. When one needs to define the control and task requirements in the Cartesian space, the problem of inverse kinematics needs to be solved. For non-redundant manipulators, a desired end-effector position and orientation can be achieved by a finite number of solutions. For redundant manipulators however, there are in general infinitely many solutions where the cardinality of the solution set must be made finite by imposing certain constraints. In this paper, we consider the Mitsubishi PA10 manipulator which is similar to the human arm, in the sense that both wrist and shoulder joints can be considered to emulate a 3DOF ball joint. We explicitly derive the analytic solution for the inverse kinematics using quaternions. Then, we derive a parameterization in terms of a pure quaternion called the swivel quaternion. The swivel quaternion is similar to the elbow swivel angle used in most approaches, but avoid the computation of inverse trigonometric functions. This parameterization of the self-motion manifold is continuous with any end-effector motion. Given the pose of the end-effector and the swivel quaternion (or swivel angle), the algorithm derives all solution of the inverse kinematics (finite number). We then show how the parameterization of the elbow self-motion can be used for the real-time control of the PA10 manipulator in the presence of obstacles.


Author(s):  
Bin Du ◽  
Jing Zhao ◽  
Chunyu Song

A mobile manipulator typically consists of a mobile platform and a robotic manipulator mounted on the platform. The base placement of the platform has a great influence on whether the manipulator can perform a given task. In view of the issue, a new approach to optimize the base placement for a specified task is proposed in this paper. Firstly, the workspace of a redundant manipulator is investigated. The manipulation capability of the redundant manipulator is maximized based on the manipulability index through the joint self-motion of the redundant manipulator. Then the maximum manipulation capability in the specified work point is determined. Next, the relative manipulability index (RMI) is defined for analyzing manipulation capability of the manipulator in its workspace, and the global manipulability map (GMM) is presented based on the above measure. Moreover, the optimal base placement related to the given task is obtained, and the motion planning is implemented by an improved rapidly-exploring random tree (RRT) algorithm with the RMI, which can enhance the manipulation capability from the initial point to the target point. Finally, the feasibility of the proposed algorithm is illustrated with numerical simulations and experiments on the mobile manipulator.


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