A Levitating Parallel Robot

Magnetic levitation may offer an alternative to traditional actuation in robotics, particularly for applications requiring minimal mechanical contact, reduced friction, and operation in sterile or sensitive environments. This paper presents a novel parallel Delta robot enhanced by magnetic levitation technology, utilizing "polarity-free magnetic repulsion" (PFR) method. Unlike conventional Delta robots that rely on mechanical joints and motors, our design integrates magnetic levitation to reduce the robot’s weight and mechanical wear. Levitation is controlled by manipulating the rotation speed of the base magnetic field, which adjusts the height of the robot’s legs using force-based dynamics rather than traditional kinematics. A mechanical low-pass-filter is used to stabilize the system. An extensive set of experiments demonstrates the feasibility of this technology in achieving high precision and stability in operations.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3611279
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

A Levitating Parallel Robot

Anderson David, Nir Shvalb, Roman Kalyna
IEEE Access
Robotic Path Planning Algorithms
article

A Levitating Parallel Robot

Anderson David, Nir Shvalb, Roman Kalyna
article en

Abstract

Magnetic levitation may offer an alternative to traditional actuation in robotics, particularly for applications requiring minimal mechanical contact, reduced friction, and operation in sterile or sensitive environments. This paper presents a novel parallel Delta robot enhanced by magnetic levitation technology, utilizing "polarity-free magnetic repulsion" (PFR) method. Unlike conventional Delta robots that rely on mechanical joints and motors, our design integrates magnetic levitation to reduce the robot’s weight and mechanical wear. Levitation is controlled by manipulating the rotation speed of the base magnetic field, which adjusts the height of the robot’s legs using force-based dynamics rather than traditional kinematics. A mechanical low-pass-filter is used to stabilize the system. An extensive set of experiments demonstrates the feasibility of this technology in achieving high precision and stability in operations.

IEEE AccessVol. 13
Ariel University (IL)
Openalex Percentile: Top 75%
Robotic Path Planning Algorithms
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