Kinematic redundancy resolution in robotic systems for energy efficiency

• We propose a novel approach for energy efficiency in redundant robotic systems. • The robot inverse kinematics is computed through the weighted pseudoinverse. • The approach optimizes the weighting matrix for the pseudoinverse computation. • We validate the approach on a 8-DOF robotic system via simulations and experiments. • Percentages of energy reduction up to 97.2% are obtained in the experimental tests. Increasing energy efficiency in automation can lead to reduced operating costs and enhanced production sustainability. In this paper, we present a novel approach for energy efficiency in redundant robotic systems. The proposed scheme aims at determining the weighting matrix used to compute the minimum-energy solution of the inverse kinematics through the weighted Jacobian pseudo-inverse. Two different solutions for computing the energy-efficient weights are proposed, one independent and the other dependent on the desired robot end-effector trajectory. The proposed approach also accounts for robot dynamics uncertainties. The performance of the approach is validated on a robotic system with 8 degrees of freedom, composed of a manipulator mounted on a linear axis. The results of extensive numerical simulations and bespoke experimental tests demonstrate the effectiveness of the proposed approach in reducing the mechanical energy consumption with respect to a state-of-the-art approach. A reduction of the energy expenditure up to 97.5% is found in the numerical tests, and up to 97.2% in the experiments, while guaranteeing robustness to imperfect knowledge of the robot dynamics parameters.

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Publication Details

Journal
Mechanism and Machine Theory
Published
2026-05-09
DOI
https://doi.org/10.1016/j.mechmachtheory.2026.106477
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
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article

Kinematic redundancy resolution in robotic systems for energy efficiency

Alessandro Gasparetto, Andrea Giusti, Lorenzo Scalera, Giuliano Fabris
Mechanism and Machine Theory
Robotic Mechanisms and Dynamics
article

Kinematic redundancy resolution in robotic systems for energy efficiency

Alessandro Gasparetto, Andrea Giusti, Lorenzo Scalera, Giuliano Fabris
article en

Abstract

• We propose a novel approach for energy efficiency in redundant robotic systems. • The robot inverse kinematics is computed through the weighted pseudoinverse. • The approach optimizes the weighting matrix for the pseudoinverse computation. • We validate the approach on a 8-DOF robotic system via simulations and experiments. • Percentages of energy reduction up to 97.2% are obtained in the experimental tests. Increasing energy efficiency in automation can lead to reduced operating costs and enhanced production sustainability. In this paper, we present a novel approach for energy efficiency in redundant robotic systems. The proposed scheme aims at determining the weighting matrix used to compute the minimum-energy solution of the inverse kinematics through the weighted Jacobian pseudo-inverse. Two different solutions for computing the energy-efficient weights are proposed, one independent and the other dependent on the desired robot end-effector trajectory. The proposed approach also accounts for robot dynamics uncertainties. The performance of the approach is validated on a robotic system with 8 degrees of freedom, composed of a manipulator mounted on a linear axis. The results of extensive numerical simulations and bespoke experimental tests demonstrate the effectiveness of the proposed approach in reducing the mechanical energy consumption with respect to a state-of-the-art approach. A reduction of the energy expenditure up to 97.5% is found in the numerical tests, and up to 97.2% in the experiments, while guaranteeing robustness to imperfect knowledge of the robot dynamics parameters.

Mechanism and Machine TheoryVol. 226
University of Udine (IT), Free University of Bozen-Bolzano (IT)
Affordable and clean energy
Openalex Percentile: Top 5%
Robotic Mechanisms and Dynamics
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