Dual Quaternion-Based Kinematic Modelling of Serial Manipulators

Author(s):  
Mohsin Dalvi ◽  
Shital S. Chiddarwar ◽  
Saumya Ranjan Sahoo ◽  
M. R. Rahul
Author(s):  
Mohsin Dalvi ◽  
Shital S. Chiddarwar ◽  
M. R. Rahul ◽  
Saumya Ranjan Sahoo

2019 ◽  
Vol 1 (2) ◽  
pp. 144-168
Author(s):  
Cristiana Miranda de Farias

In this paper, the well known recursive Newton-Euler inverse dynamics algorithm for serial manipulators is reformulated into the context of the algebra of Dual Quaternions. Here we structure the forward kinematic description with screws and line displacements rather than the well established Denavit-Hartemberg parameters, thus accounting better efficiency, compactness and simpler dynamical models. We also present here the closed solution for the dqRNEA, and to do so we formalize some of the algebra for dual quaternion-vectors and dual quaternion-matrices. With a closed formulation of the dqRNEA we also create a dual quaternion based formulation for the computed torque control, a feedback linearization method for controlling a serial manipulator's torques in the joint space. Finally, a cost analysis of the main Dual Quaternions operations and of the Newton-Euler inverse dynamics algorithm as a whole is made and compared with other results in the literature.


2021 ◽  
pp. 1-1
Author(s):  
Michael Fennel ◽  
Antonio Zea ◽  
Johannes Mangler ◽  
Arne Roennau ◽  
Uwe D. Hanebeck

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110144
Author(s):  
Qianqian Zhang ◽  
Daqing Wang ◽  
Lifu Gao

To assess the inverse kinematics (IK) of multiple degree-of-freedom (DOF) serial manipulators, this article proposes a method for solving the IK of manipulators using an improved self-adaptive mutation differential evolution (DE) algorithm. First, based on the self-adaptive DE algorithm, a new adaptive mutation operator and adaptive scaling factor are proposed to change the control parameters and differential strategy of the DE algorithm. Then, an error-related weight coefficient of the objective function is proposed to balance the weight of the position error and orientation error in the objective function. Finally, the proposed method is verified by the benchmark function, the 6-DOF and 7-DOF serial manipulator model. Experimental results show that the improvement of the algorithm and improved objective function can significantly improve the accuracy of the IK. For the specified points and random points in the feasible region, the proportion of accuracy meeting the specified requirements is increased by 22.5% and 28.7%, respectively.


2020 ◽  
Vol 53 (2) ◽  
pp. 9316-9321
Author(s):  
Giulia Michieletto ◽  
Nicola Lissandrini ◽  
Andrea Antonello ◽  
Riccardo Antonello ◽  
Angelo Cenedese
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