Soft Robotics - Design and Applications: Investigating Soft Robotics Design Principles and Applications for Developing Robots With Compliant and Flexible Structures

Authors

  • Dr. Elena Rodriguez Research Scientist in Machine Learning, Stanford University, California, USA

Keywords:

soft robotics, compliant robots, flexible structures, design principles, applications, healthcare, exploration, manufacturing, challenges, future directions

Abstract

Soft robotics is a rapidly growing field that explores the design and development of robots with compliant and flexible structures. These robots, inspired by biological systems, offer unique advantages in various applications due to their ability to interact safely with humans and delicate environments. This paper presents an overview of soft robotics design principles and highlights key applications in diverse fields such as healthcare, exploration, and manufacturing. We discuss the challenges and opportunities in soft robotics research and suggest future directions for advancing this exciting field.

References

Pargaonkar, Shravan. "A Review of Software Quality Models: A Comprehensive Analysis." Journal of Science & Technology 1.1 (2020): 40-53.

Raparthi, Mohan, Sarath Babu Dodda, and SriHari Maruthi. "Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks." European Economic Letters (EEL) 10.1 (2020).

Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.

Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).

Pargaonkar, Shravan. "Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering." Journal of Science & Technology 1.1 (2020): 67-81.

Vyas, Bhuman. "Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.1 (2021): 59-62.

Pargaonkar, Shravan. "Quality and Metrics in Software Quality Engineering." Journal of Science & Technology 2.1 (2021): 62-69.

Pargaonkar, Shravan. "The Crucial Role of Inspection in Software Quality Assurance." Journal of Science & Technology 2.1 (2021): 70-77.

Vyas, Bhuman. "Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach." International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068 1.1 (2022): 66-70.

Rajendran, Rajashree Manjulalayam. "Scalability and Distributed Computing in NET for Large-Scale AI Workloads." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.2 (2021): 136-141.

Pargaonkar, Shravan. "Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development." Journal of Science & Technology 2.1 (2021): 78-84.

Vyas, Bhuman. "Ethical Implications of Generative AI in Art and the Media." International Journal for Multidisciplinary Research (IJFMR), E-ISSN: 2582-2160.

Rajendran, Rajashree Manjulalayam. "Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 11.1 (2022): 292-297.

Pargaonkar, Shravan. "Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality." Journal of Science & Technology 2.1 (2021): 85-94.

Pargaonkar, S. (2020). A Review of Software Quality Models: A Comprehensive Analysis. Journal of Science & Technology, 1(1), 40-53.

Raparthi, M., Dodda, S. B., & Maruthi, S. (2020). Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks. European Economic Letters (EEL), 10(1).

Pargaonkar, S. (2020). Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering. Journal of Science & Technology, 1(1), 61-66.

Raparthi, M., Dodda, S. B., & Maruthi, S. (2021). AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health. European Economic Letters (EEL), 11(1).

Vyas, B. (2021). Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(1), 59-62.

Rajendran, R. M. (2021). Scalability and Distributed Computing in NET for Large-Scale AI Workloads. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(2), 136-141.

Pargaonkar, S. (2020). Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering. Journal of Science & Technology, 1(1), 67-81.

Vyas, B. (2022). Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 1(1), 66-70.

Pargaonkar, S. (2021). Quality and Metrics in Software Quality Engineering. Journal of Science & Technology, 2(1), 62-69.

Vyas, B. Ethical Implications of Generative AI in Art and the Media. International Journal for Multidisciplinary Research (IJFMR), E-ISSN, 2582-2160.

Rajendran, R. M. (2022). Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 11(1), 292-297.

Pargaonkar, S. (2021). The Crucial Role of Inspection in Software Quality Assurance. Journal of Science & Technology, 2(1), 70-77.

Pargaonkar, S. (2021). Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development. Journal of Science & Technology, 2(1), 78-84.

Pargaonkar, S. (2021). Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality. Journal of Science & Technology, 2(1), 85-94.

Cover

Downloads

Published

26-02-2024

How to Cite

[1]
D. E. Rodriguez, “Soft Robotics - Design and Applications: Investigating Soft Robotics Design Principles and Applications for Developing Robots With Compliant and Flexible Structures”, J. Computational Intel. & Robotics, vol. 2, no. 1, pp. 1–9, Feb. 2024.

Issue

Vol. 2 No. 1 (2022): Journal of Computational Intelligence and Robotics

Section

Articles

License

Creative Commons 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.