Quantum computation for robot posture optimization
Abstract Quantum computing has gained attention for its potential to surpass classical computing in large-scale computations. In this study, we propose a method for solving the inverse kinematics of a robot using quantum computing. The approach leverages the ability of qubits to represent points on...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-12109-0 |
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| _version_ | 1849763336473804800 |
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| author | Takuya Otani Atsuo Takanishi Nobuyuki Hara Yutaka Takita Koichi Kimura |
| author_facet | Takuya Otani Atsuo Takanishi Nobuyuki Hara Yutaka Takita Koichi Kimura |
| author_sort | Takuya Otani |
| collection | DOAJ |
| description | Abstract Quantum computing has gained attention for its potential to surpass classical computing in large-scale computations. In this study, we propose a method for solving the inverse kinematics of a robot using quantum computing. The approach leverages the ability of qubits to represent points on a sphere in three-dimensional space. Forward kinematics calculations are performed using qubits that encode the posture of each robot link, while inverse kinematics solutions are obtained through iterative optimization on a classical computer. Furthermore, we demonstrate that the robot’s end-effector position can be effectively represented using a 2-qubit rotation gate, where the root joint angle influences the tip joint angle, resulting in accelerated convergence during inverse kinematics optimization. The proposed method was validated on an actual quantum computer, confirming its feasibility and efficiency. These findings suggest that hybrid quantum-classical approaches can enhance robotic motion planning and optimization in future quantum computing applications. |
| format | Article |
| id | doaj-art-651a846641024b9fa6f2d60c55e57e91 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-651a846641024b9fa6f2d60c55e57e912025-08-20T03:05:26ZengNature PortfolioScientific Reports2045-23222025-08-0115111110.1038/s41598-025-12109-0Quantum computation for robot posture optimizationTakuya Otani0Atsuo Takanishi1Nobuyuki Hara2Yutaka Takita3Koichi Kimura4College of Systems Engineering and Science, Shibaura Institute of TechnologyDepartment of Modern Mechanical Engineering, Waseda UniversityFujitsu LtdFujitsu LtdFujitsu LtdAbstract Quantum computing has gained attention for its potential to surpass classical computing in large-scale computations. In this study, we propose a method for solving the inverse kinematics of a robot using quantum computing. The approach leverages the ability of qubits to represent points on a sphere in three-dimensional space. Forward kinematics calculations are performed using qubits that encode the posture of each robot link, while inverse kinematics solutions are obtained through iterative optimization on a classical computer. Furthermore, we demonstrate that the robot’s end-effector position can be effectively represented using a 2-qubit rotation gate, where the root joint angle influences the tip joint angle, resulting in accelerated convergence during inverse kinematics optimization. The proposed method was validated on an actual quantum computer, confirming its feasibility and efficiency. These findings suggest that hybrid quantum-classical approaches can enhance robotic motion planning and optimization in future quantum computing applications.https://doi.org/10.1038/s41598-025-12109-0 |
| spellingShingle | Takuya Otani Atsuo Takanishi Nobuyuki Hara Yutaka Takita Koichi Kimura Quantum computation for robot posture optimization Scientific Reports |
| title | Quantum computation for robot posture optimization |
| title_full | Quantum computation for robot posture optimization |
| title_fullStr | Quantum computation for robot posture optimization |
| title_full_unstemmed | Quantum computation for robot posture optimization |
| title_short | Quantum computation for robot posture optimization |
| title_sort | quantum computation for robot posture optimization |
| url | https://doi.org/10.1038/s41598-025-12109-0 |
| work_keys_str_mv | AT takuyaotani quantumcomputationforrobotpostureoptimization AT atsuotakanishi quantumcomputationforrobotpostureoptimization AT nobuyukihara quantumcomputationforrobotpostureoptimization AT yutakatakita quantumcomputationforrobotpostureoptimization AT koichikimura quantumcomputationforrobotpostureoptimization |