Applications of Dynamic Models for Cable-Driven Parallel Robots: A Comprehensive Review
Year: 2025
Type: article
Abstract: Cable-driven parallel robots (CDPR) represent an emerging field of research that has vast applications across different fields of science and engineering, such as medical, aerospace, construction, etc. Dynamic modeling plays an important role in understanding the behavior of these complex systems as well as in enhancing their performances. The state of the art in cable-driven parallel robots (CDPRs) is thoroughly summarized in this review, which covers both basic ideas and cutting-edge advancements in a variety of design modeling control and application domains. The study starts with a thorough examination of the geometric layout and essential elements of CDPR systems describing how the special arrangement of flexible cables allows for better workspace scalability and dynamic performance. It also looks at the complex kinematic and dynamic models that portray the nonlinear behaviors that are essential for attaining accurate motion control like cable sagging elasticity and friction. The optimization of workspace and tension distribution is prioritized in order to preserve system stability and energy efficiency. Furthermore, the review looks at a number of control and planning strategies such as motion planning methods and advanced algorithms like reinforcement learning which guarantee reliable trajectory tracking and operational safety. The wide-ranging effects of CDPR technology are demonstrated through a variety of case studies in the fields of construction entertainment, medical care, agriculture, disaster response, material handling, and space research. Lastly, new developments that promise to improve the capabilities and uptake of CDPRs in next-generation robotic systems are explored, including the incorporation of artificial intelligence machine learning and innovative materials.
Source: Nelineinaya Dinamika
DOI: 10.20537/nd251101
Authors: M. J. Tachia, A. V. Maloletov
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7117136226