Singularity avoidance method for dual-arm closed-chain system based on damped least squares

IF 2.3 4区 计算机科学 Q2 Computer Science International Journal of Advanced Robotic Systems Pub Date : 2023-09-01 DOI:10.1177/17298806231206940
Qin Zhang, Zhenyu Liu, Hui Chai, Yueyang Li
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引用次数: 0

Abstract

When two manipulators cooperate to clamp a rigid object, a closed chain with both ends fixed is formed. The singularity of a single manipulator causes the closed chain to be at a singularity, which results in uncertainty in the velocity mapping between the terminal and joint space. This study proposes a closed-chain singularity processing method for dual-arm collaboration, adopting the Jacobian pseudoinverse method based on damped least squares to obtain an approximate solution. During the solution process, the adaptive damping factor is improved by cubic polynomials, and the optimal damping factor is determined by quadratic sequence programming. Furthermore, this study analyzes the kinematic constraints of the closed-chain system and constructs a closed-chain Jacobian to judge whether the system is in a singular region. Finally, the effectiveness of the proposed method is verified through simulations.
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基于阻尼最小二乘的双臂闭链系统奇异避免方法
当两个机械手合作夹紧一个刚性物体时,就形成了一个两端固定的封闭链条。单个机械臂的奇异性导致闭合链处于奇异点,从而导致末端与关节空间之间速度映射的不确定性。提出了一种双臂协作的闭链奇点处理方法,采用基于阻尼最小二乘的雅可比伪逆方法得到近似解。在求解过程中,采用三次多项式对自适应阻尼因子进行改进,采用二次序列规划确定最优阻尼因子。进一步分析了闭链系统的运动约束条件,构造了闭链雅可比矩阵来判断系统是否处于奇异区域。最后,通过仿真验证了所提方法的有效性。
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来源期刊
CiteScore
6.50
自引率
0.00%
发文量
65
审稿时长
6 months
期刊介绍: International Journal of Advanced Robotic Systems (IJARS) is a JCR ranked, peer-reviewed open access journal covering the full spectrum of robotics research. The journal is addressed to both practicing professionals and researchers in the field of robotics and its specialty areas. IJARS features fourteen topic areas each headed by a Topic Editor-in-Chief, integrating all aspects of research in robotics under the journal''s domain.
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