Redundant robot trajectory optimization via a kinematic approximation approach

Many industrial robot applications are functionally redundant, so the robot kinematic chain has more degrees of freedom than the ones required by the task. This feature can be exploited to optimize the task by choosing convenient robot configurations at the working points, according to a design goal. In this paper, the case of a SCARA robot performing a redundant task along an assigned path is considered. A novel trajectory optimization technique is presented, which relies on the kinematic model and on the choice of a single parameter, thus reducing the computational effort. Numerical results are discussed.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-25
DOI
https://doi.org/10.5281/zenodo.14731149
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.00
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article

Redundant robot trajectory optimization via a kinematic approximation approach

Zenodo (CERN European Organization for Nuclear Research)
Robotic Mechanisms and Dynamics
article

Redundant robot trajectory optimization via a kinematic approximation approach

article en

Abstract

Many industrial robot applications are functionally redundant, so the robot kinematic chain has more degrees of freedom than the ones required by the task. This feature can be exploited to optimize the task by choosing convenient robot configurations at the working points, according to a design goal. In this paper, the case of a SCARA robot performing a redundant task along an assigned path is considered. A novel trajectory optimization technique is presented, which relies on the kinematic model and on the choice of a single parameter, thus reducing the computational effort. Numerical results are discussed.

Zenodo (CERN European Organization for Nuclear Research)
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Robotic Mechanisms and Dynamics
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Redundant robot trajectory optimization via a kinematic approximation approach · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS