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Multiobjective Kinematic Trajectory Planning An Application to the Captive Trajectory Simulation (CTS) System.

机译:多目标运动轨迹规划在运动轨迹仿真(CTS)系统中的应用。

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摘要

In this thesis, a new approach to the resolution of multiobjective trajectory planning problems is proposed. Rather than providing a single solution with the weighting method, it is proposed to provide the entire Pareto optimal set, or more generally the entire minimal element set when the objective space is partially ordered by a cone. This approach is applied to the general class of multiobjective deterministic finite horizon optimal control problems to which many multiobjective trajectory planning problems, including the joint space trajectory planning problem arising from a wind-tunnel experimental setup called captive trajectory simulation (CTS) system, can be shown to belong. A new discrete dynamic programming (DDP) approximation method for the resolution of this class of problems is developed, from which an approximate minimal element set is obtained. Partial convergence results of this approximate set towards the original minimal element set is obtained using set convergence in the sense of Hausdorff. When the DDP approximation method is applied to the joint trajectory planning problem for the CTS system, the approximate Pareto optimal set is shown to provide a better representation of the Pareto optimal set than the set obtained with the weighting method. In order to improve the computational efficiency of the DDP approximation method, a clustering approach is introduced. With the application of clustering, the DDP approximation method is shown to have polynomial complexity, which yields a dramatic reduction in the resolution time. The resulting set is shown to still provide a better representation of the Pareto optimal set than the set obtained with the weighting method. The Hausdorff distance is proposed as a measure for comparison. Finally, the complete CTS trajectory planning problem is solved by sequentially solving the problem in the task and joint spaces. For the resolution of the task space problem, an algorithm based on the resolution of a rural postman problem is proposed. The proposed sequential approach for the resolution of the CTS trajectory planning problem allows for fast resolution times.
机译:本文提出了一种解决多目标轨迹规划问题的新方法。提议用权重方法来提供单个解决方案,而不是提供整个帕累托最优集合,或更普遍地,当目标空间由圆锥部分排序时,提供整个最小元素集。这种方法适用于一般类别的多目标确定性有限水平最优控制问题,可以解决许多多目标轨迹规划问题,包括由称为“俘虏轨迹模拟”(CTS)系统的风洞实验装置引起的联合空间轨迹规划问题。显示属于。开发了一种用于解决此类问题的新的离散动态规划(DDP)逼近方法,从该方法中可以获取近似的最小元素集。在Hausdorff的意义上,使用集收敛可以得到该近似集对原始最小元素集的部分收敛结果。当将DDP近似方法应用于CTS系统的联合轨迹规划问题时,与通过加权方法获得的集合相比,显示了近似的Pareto最优集合可以更好地表示Pareto最优集合。为了提高DDP近似方法的计算效率,引入了一种聚类方法。随着聚类的应用,DDP逼近方法被证明具有多项式复杂度,从而大大缩短了解析时间。结果表明,与使用加权方法获得的集合相比,所得集合仍可以更好地表示帕累托最优集合。提出了Hausdorff距离作为比较的量度。最后,通过依次解决任务和关节空间中的问题,解决了完整的CTS轨迹规划问题。为了解决任务空间问题,提出了一种基于农村邮递员问题解决的算法。提出的解决CTS轨迹规划问题的顺序方法可加快解决速度。

著录项

  • 作者

    Guigue, Alexis.;

  • 作者单位

    Carleton University (Canada).;

  • 授予单位 Carleton University (Canada).;
  • 学科 Applied Mathematics.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 226 p.
  • 总页数 226
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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