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TRAC-IK: An open-source library for improved solving of generic inverse kinematics

Beeson, Patrick, Ames, Barrett·2015·2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids)

Abstract

The Inverse Kinematics (IK) algorithms implemented in the open-source Orocos Kinematics and Dynamics Library (KDL) are arguably the most widely-used generic IK solvers worldwide. However, KDL's only joint-limit-constrained IK implementation, a pseudoinverse Jacobian IK solver, repeatedly exhibits false-negative failures on various humanoid platforms. In order to find a better IK solver for generic manipulator chains, a variety of open-source, drop-in alternatives have been implemented and evaluated for this paper. This article provides quantitative comparisons, using multiple humanoid platforms, between an improved implementation of the KDL inverse Jacobian algorithm, a set of sequential quadratic programming (SQP) IK algorithms that use a variety of quadratic error metrics, and a combined algorithm that concurrently runs the best performing SQP algorithm and the improved inverse Jacobian implementation. The best alternative IK implementation finds solutions much more often than KDL, is faster on average than KDL for typical manipulation chains, and (when desired) allows tolerances on each Cartesian dimension, further improving speed and convergence when an exact Cartesian pose is not possible and/or necessary.

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Metadata

Authors
Beeson, P., & Ames, B.
Venue
2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids)
Publisher
IEEE
Published
2015-11
Pages
928-935
OpenAlex
W2205340216
Cited by
355
References
10
FWCI
19.70
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: TRAC-IK: An open-source library for improved solving of generic inverse kinematics. https://app.cochat.ai/papers/10.1109/humanoids.2015.7363472
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Beeson, P., & Ames, B. (2015). TRAC-IK: An open-source library for improved solving of generic inverse kinematics. 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids). https://doi.org/10.1109/humanoids.2015.7363472

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