Purpose <p>This paper reviews cable-driven parallel robots (CDPRs), emphasizing their applications, design innovations, and emerging AI-driven control methods. It highlights CDPR advantages (large workspace, rigidity, load capacity) and synthesizes recent research to guide future developments in robotics and automation.</p> Methodology <p>The study analyzes CDPR applications across industries and innovative structural designs, discusses kinematic/dynamic modeling, identifies key performance indicators (workspace, stiffness), and reviews control/trajectory planning methods. It focuses on AI techniques (deep learning, iterative learning) for addressing control challenges.</p> Results <p>CDPRs excel in precision and adaptability but rely on tension management and optimized designs. Kinematic/dynamic models ensure stability, while AI enhances control robustness and real-time trajectory optimization, overcoming system nonlinearities and uncertainties.</p> Conclusions <p>This review summarizes cable-driven parallel robots' design, modeling, performance optimization, and control. Future research should focus on reconfigurable structures, new materials, and AI-driven control to enhance workspace, stiffness, and accuracy.</p>