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Dynamic obstacles are addressed through IDWA-based trajectory prediction, while the SDBO\u2013IDWA algorithm optimizes obstacle avoidance trajectories for suspended objects. Furthermore, leveraging force\u2013position cooperative optimization, the method resolves coupled kinematic and dynamic constraints inherent in MCSS. Simulation and experimental results demonstrate that the SDBO\u2013IDWA algorithm outperforms traditional approaches, achieving a 19.95% reduction in minimum trajectory length and a 57.77% decrease in runtime for suspended objects. For towing robots, it reduces optimal trajectory length by 9.52% and fitness values by 9.44%. 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