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Cited by 349

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

A complete generalized solution to the inverse kinematics of robots

Goldenberg, A., Benhabib, B., Fenton, R.·1985·IEEE Journal on Robotics and Automation

Abstract

The kinematic transformation between task space and joint configuration coordinates is nonlinear and configuration dependent. A solution to the inverse kinematics is a vector of joint configuration coordinates that corresponds to a set of task space coordinates. For a class of robots closed form solutions always exist, but constraints on joint displacements cannot be systematically incorporated in the process of obtaining a solution. An iterative solution is presented that is suitable for any class of robots having rotary or prismatic joints, with any arbitrary number of degrees of freedom, including both standard and kinematically redundant robots. The solution can be obtained subject to specified constraints and based on certain performance criteria. The solution is based on a new rapidly convergent constrained nonlinear optimization algorithm which uses a modified Newton-Raphson technique for solving a system nonlinear equations. The algorithm is illustrated using as an example a kinematically redundant robot.

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Metadata

Authors
Goldenberg, A., Benhabib, B., & Fenton, R.
Venue
IEEE Journal on Robotics and Automation
Published
1985
Volume
1
Issue
1
Pages
14-20
ISSN
0882-4967 (ISSN-L)
OpenAlex
W2159806973
Cited by
349
References
10
FWCI
19.43
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A complete generalized solution to the inverse kinematics of robots. https://app.cochat.ai/papers/10.1109/jra.1985.1086995
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Goldenberg, A., Benhabib, B., & Fenton, R. (1985). A complete generalized solution to the inverse kinematics of robots. IEEE Journal on Robotics and Automation. https://doi.org/10.1109/jra.1985.1086995

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.