Soft Robotics - Design and Applications: Investigating Soft Robotics Design Principles and Applications for Developing Robots With Compliant and Flexible Structures
Keywords:
soft robotics, compliant robots, flexible structures, design principles, applications, healthcare, exploration, manufacturing, challenges, future directionsAbstract
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.
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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.
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