{"title":"Combining grasping and rotation with a spherical robot hand mechanism","authors":"Vatsal V. Patel, Aaron M. Dollar","doi":"10.1038/s42256-025-01039-1","DOIUrl":null,"url":null,"abstract":"Object reorientation is a key functionality in dexterous manipulation tasks, such as turning a doorknob. This is usually done on robot arms with a simple gripper and a three-degrees-of-freedom wrist. However, wrists are mechanically complex, and the wrist axes are often far away from the grasped object, resulting in coupled translations that need to be compensated with awkward whole-arm motions. We present a robot hand mechanism based on a spherical parallel architecture that can both grasp and rotate a wide range of objects in all three axes, combining much of the function of traditional wrists and grippers. The hand mechanism allows for pure spherical rotations of the grasped object about a known fixed point close to the object, thereby avoiding parasitic translations and inefficient arm motions. This point also stays fixed with respect to the hand, and is independent of the object shape, pose or initial grasp. We detail the spherical parallel design and workspace model of the wrist-like Sphinx hand, validate its performance for lower-degrees-of-freedom robot arms without traditional wrists and show that it can accurately rotate the grasped objects over large angles with basic open-loop control. Developing robot hands for unstructured human environments is a major challenge. A robotic hand that combines grasping and wrist-like rotation in one mechanism for more efficient and versatile object manipulation is presented.","PeriodicalId":48533,"journal":{"name":"Nature Machine Intelligence","volume":"7 7","pages":"999-1009"},"PeriodicalIF":23.9000,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Machine Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.nature.com/articles/s42256-025-01039-1","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Object reorientation is a key functionality in dexterous manipulation tasks, such as turning a doorknob. This is usually done on robot arms with a simple gripper and a three-degrees-of-freedom wrist. However, wrists are mechanically complex, and the wrist axes are often far away from the grasped object, resulting in coupled translations that need to be compensated with awkward whole-arm motions. We present a robot hand mechanism based on a spherical parallel architecture that can both grasp and rotate a wide range of objects in all three axes, combining much of the function of traditional wrists and grippers. The hand mechanism allows for pure spherical rotations of the grasped object about a known fixed point close to the object, thereby avoiding parasitic translations and inefficient arm motions. This point also stays fixed with respect to the hand, and is independent of the object shape, pose or initial grasp. We detail the spherical parallel design and workspace model of the wrist-like Sphinx hand, validate its performance for lower-degrees-of-freedom robot arms without traditional wrists and show that it can accurately rotate the grasped objects over large angles with basic open-loop control. Developing robot hands for unstructured human environments is a major challenge. A robotic hand that combines grasping and wrist-like rotation in one mechanism for more efficient and versatile object manipulation is presented.
期刊介绍:
Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements.
To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects.
Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.