上海交通大学学报

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多机协调悬吊系统的矢量碰撞检测算法(网络首发)

  

  1. 兰州交通大学机电工程学院
  • 基金资助:
    国家自然科学基金项目(51965032);甘肃省自然科学基金重点项目(22JR5RA319);甘肃省优秀博士生项目(23JRRA842);

Vector collision detection algorithm for multi-crane coordinated suspension system

  1. (School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

摘要: 针对传统碰撞检测算法不能完美适配多机协调悬吊系统轨迹规划中碰撞检测的问题,提出了一种基于矢量构建的全面考虑悬吊系统碰撞风险的检测算法。首先,针对柔索出现的悬链线效应,提出了柔索优化模型,并根据不同碰撞类型给出相应的检测策略。然后,在模型优化策略基础上提出了基于点、矢量、角度线性组合的矢量碰撞检测算法及优化方法。仿真结果表明,该算法准确而高效地实现了8次有效碰撞检测,验证了两种不同碰撞类型优化策略的合理性。最后,柔索的等效弹性应变和等效应力的变化进一步验证了该算法具有不错的碰撞检测精度和效率,所提矢量碰撞检测算法在复杂悬吊环境中能够更好地适配多机协调悬吊系统,为后续悬吊系统的避障轨迹规划提供了可行方法参考。

关键词: 多机协调悬吊系统, 碰撞检测算法, 模型优化, 柔索驱动

Abstract: Aiming at the problem that traditional collision detection algorithms can’t perfectly adapt to collision detection in trajectory planning of multi-crane coordinated suspension system, a vector-based detection algorithm that comprehensively considers the collision risk of the suspension system is proposed. First, in view of the catenary effect appearing in the cable, an optimization model of the cable is proposed, and corresponding detection strategies are given according to different collision types. Then, based on the model optimization strategy, a vector collision detection algorithm and optimization method based on linear combination of points, vectors, and angles are proposed. The simulation results show that the algorithm accurately and efficiently achieves 8 effective collision detections, verifying the rationality of the optimization strategies for two different collision types. Finally, equivalent elastic strain and equivalent stress of the cables further verify that the algorithm has good collision detection accuracy and efficiency, the proposed vector collision detection algorithm can better adapt to the multi-crane coordinated suspension system in complex suspension environments and provides a feasible method reference for subsequent obstacle avoidance trajectory planning of the suspension system.

Key words: Multi-crane coordinated suspension system, collision detection algorithm, model optimization, cable-driven

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