2023
DOI: 10.3934/acse.2023006
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Numerically stable solution to the 6R problem of Inverse Kinematics

Abstract: In this paper, a stable and accurate algorithm to compute all solutions of the inverse kinematics problem of a 6 revolute manipulator chain is presented. A system of equations is constructed based on the fundamental closure conditions, leading to a closed algebraic system of 20 equations involving 16 quantities, composed of trigonometric functions of five among the six unknown joint angles. Two among these five are stably eliminated using singular value decomposition (SVD) avoiding the need to consider special… Show more

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Cited by 4 publications
(6 citation statements)
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“…R6B6 can generate cycles without requirement for bonds with dependent dihedrals to form coterminal pairs. 36,37 However, currently the R6B6 source code is not publicly available.…”
Section: Generating Cycles With Inverse Kinematicsmentioning
confidence: 99%
See 3 more Smart Citations
“…R6B6 can generate cycles without requirement for bonds with dependent dihedrals to form coterminal pairs. 36,37 However, currently the R6B6 source code is not publicly available.…”
Section: Generating Cycles With Inverse Kinematicsmentioning
confidence: 99%
“…Significant progress in using IK to generate cyclic molecules was achieved by Coutsias et al [35][36][37] Due to his efforts, there have been implemented two ring closure algorithms for sampling molecular conformers: TLC (Triaxial loop closure) 35 and R6B6 (6 rotors/6 bar). 36,37 To the best of our knowledge, these two programs exhaust the list of existing IK ring closure codes for chemical purposes.…”
Section: Generating Cycles With Inverse Kinematicsmentioning
confidence: 99%
See 2 more Smart Citations
“…Typical numerical approaches use Jacobian methods [14], [15] to iteratively find the inverse kinematics solution for a desired pose around the current robot configuration. Inverse or pseudo-inverse Jacobian, or singular value decomposition (SVD) [16] computations are expensive and especially prone to getting stuck in local minima. Recent approaches like TracIK [17] and BioIK [18] have mitigated these problems to an extent using random restarts with nonlinear optimization, and memetic algorithms that combine gradient-based optimization with genetic and particle swarm optimization, respectively.…”
Section: Related Workmentioning
confidence: 99%