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A novel inverse kinematics for solving repetitive motion planning of 7-DOF SRS manipulator. ROBOTICA 2022. [DOI: 10.1017/s0263574722001370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
The repetitive motion planning movements of the redundant manipulator will cause oscillations and unintended swings of joints, which increase the risk of collisions between the manipulator and its surroundings. Motivated by this phenomenon, this paper presents an inverse kinematics algorithm for the spherical-revolute-spherical manipulator to solve the paradox raised by joint-drift and control the pose with no swing of the elbow. This algorithm takes the joint Cartesian positions set as the intermediary and divides the inverse solution process into two mapping processes within joint limits. Simulations are executed to evaluate this algorithm, and the results show this algorithm is applicable to repetitive motion planning and is capable of producing superior configurations based on its real-time ability and stable solve rate. Experiments using the 7-degree-of-freedom spherical-revolute-spherical manipulator demonstrate the effectiveness of this algorithm to remedy the joint-drift and elbow swing compared to Kinematics and Dynamics Library and TRAC-IK.
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Liu B, Sha L, Huang K, Zhang W, Yang H. A topology optimization method for collaborative robot lightweight design based on orthogonal experiment and its applications. INT J ADV ROBOT SYST 2022. [DOI: 10.1177/17298814211056143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Topology optimization is an effective method for the lightweight of collaborative robots. The extreme working conditions of the robot for the existing topology optimization approach are usually determined by design experience, which may cause mismatch between the chosen load boundary condition of the parts to be optimized and the actual maximum one. In this article, a kind of topology optimization method based on orthogonal experiment was proposed to avoid this mismatch. For this method, the extreme working condition of robots was determined by finding out the combination of robot joint angles when the stress of the part was maximum based on orthogonal experiment. And then, the structure of the part was optimized with the objective of minimizing mass and the constraint of the maximum end displacement of the robots. Finally, the proposed method and the existing method were applied to the lightweight design of a 7 degree of freedom upper limb powered exoskeleton robot, and the results demonstrated that the presented approach can reduce 6.78% maximum end displacement of the robot on average compared with the existing one. It can be concluded that the proposed method in this article is more reasonable and applicable to the structure optimization of collaborative robots.
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Affiliation(s)
- Bin Liu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, Jiangsu, China
| | - Liansen Sha
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, Jiangsu, China
| | - Kun Huang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, Jiangsu, China
| | - Wenbin Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Hongbo Yang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, Jiangsu, China
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