AI-Powered Robotics for Enhancing Productivity in American Manufacturing: Innovations and Case Studies
Abstract
Robots are electro-mechanical agents that can be programmed to accomplish repetitive tasks. "AI-Powered robotics" refers to these same robots enhanced with various capacities for data processing, AI, and decision-making. They may be categorized into three groups: semi-autonomous robots, which can perform some tasks partially on their own; exoskeleton robots, for which the robot augments a human's capabilities; and autonomous or AI-robots, which can function completely independently. It is these autonomous robots that are the focus of our work. As a class, AI-Training-Data-Powered Robots (AITDPR) are either physically separated from humans in a high-dimensional workspace or are extensively tested throughout their workspace with verified reliability throughout their operational envelope. AITDPR can autonomously carry out various manufacturing tasks that may involve the manipulation and assembly of objects in high-dimensional shared spaces.
Downloads
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
License Terms
Ownership and Licensing:
Authors of this research paper submitted to the journal owned and operated by The Science Brigade Group retain the copyright of their work while granting the journal certain rights. Authors maintain ownership of the copyright and have granted the journal a right of first publication. Simultaneously, authors agreed to license their research papers under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.
License Permissions:
Under the CC BY-NC-SA 4.0 License, others are permitted to share and adapt the work, as long as proper attribution is given to the authors and acknowledgement is made of the initial publication in the Journal. This license allows for the broad dissemination and utilization of research papers.
Additional Distribution Arrangements:
Authors are free to enter into separate contractual arrangements for the non-exclusive distribution of the journal's published version of the work. This may include posting the work to institutional repositories, publishing it in journals or books, or other forms of dissemination. In such cases, authors are requested to acknowledge the initial publication of the work in this Journal.
Online Posting:
Authors are encouraged to share their work online, including in institutional repositories, disciplinary repositories, or on their personal websites. This permission applies both prior to and during the submission process to the Journal. Online sharing enhances the visibility and accessibility of the research papers.
Responsibility and Liability:
Authors are responsible for ensuring that their research papers do not infringe upon the copyright, privacy, or other rights of any third party. The Science Brigade Publishers disclaim any liability or responsibility for any copyright infringement or violation of third-party rights in the research papers.
