Papers
7
Total Citations
58
H-Index
4
About
Da Song is a leading researcher in the field of cable-driven parallel robots (CDPRs) and haptic interactive systems, with a focus on advancing real-time control, tension distribution, and human-robot interaction. Their most cited work, "Configuration Optimization and a Tension Distribution Algorithm for Cable-Driven Parallel Robots" (2018, 32 citations), introduces a convex analysis method to optimize CDPR configurations and ensure continuous tension distribution during trajectory tracking—a critical step for improving robot performance. Song’s subsequent contributions include a novel real-time tension distribution method (2024, 6 citations) that overcomes the limitations of iterative algorithms, and a haptic interactive robot control strategy (2023, 8 citations) that enhances motion accuracy and stability using ball screw-driven cables. Their work also extends to astronaut virtual training, where they developed velocity planning under high-order dynamic constraints (2020, 6 citations), and to innovative robot designs, such as a cable-driven serial robot based on flexible joints and tensegrity structures (2025). With over 50 total citations, Song’s research is driving safer, more responsive robots for complex dynamic environments and human-robot collaboration.
Research Focus
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