标题: | 利用位能场模型作路径规划及物体形状比对 Potential-based Path Planning and Shape Matching |
作者: | 林建州 庄仁辉 资讯科学与工程研究所 |
关键字: | 路径规划;广义位能场;形状比对;避碰;机械人;path planning;generalized potential field;shape matching;collision avoidance;robot |
公开日期: | 2004 |
摘要: | 本博士論文乃利用位能场模型來呈现自由空间的方法,探讨位能场于不同问题的应用。我们提出數个以位能场模型为基础的演算法來协助解决(1)机器人路径规划与(2)物体形狀比对的问题。在这些演算法中,其共同的主要概念是将物体及自由空间的边界带相同之电性后,静止的自由空间会有位能场形成,且自由空间对物体产生推斥力,再将作用于物体上的推斥力作为物体移动的推力与转动的转矩,使物体降低在自由空间中位能与自由空间达成最佳的形狀比对,物体的形式可以是刚体或是連结物。最佳的形狀比对可藉由调整物体的位置、姿态來降低位能而达成。 在机械手臂路径规划研究中,我们探讨了利用牛顿位能场应用于二维路径规划问题的可行性。在研究中,我们将机械手臂及自由空间的边界以均匀或不均匀的带电后,如同于电学中的定义,可计算得知机械手臂在工作空间中所受的斥力与转矩,藉由这些斥力与转矩來调整手臂于自由空间之组态使其位能降低。透过寻找这一連串的组态后,一条避碰的路径即可由这些一系列组态來构成。我们也将上述演算法推广到三维工作空间,亦即将原來牛顿位能场模型用三维广义位能场[1] 來取代。 在 [1] 中提到,牛顿位能场模型在三维空间之中会造成物体撞入障碍物中,并不能达到避碰的要求。因而,我们采用广义位能场模型來达成避碰。相对于机械手臂的基点是固定的,連结型机器人因有可移动的基点所以在路经规划上有较高的自由度。在本論文中,我们亦发展了相对应之路径规划演算法。 另外,透过相同的广义位能场模型的建立,我们亦提出一三维物体形狀比对的演算法。在 [2] 中,广义位能场模型被用來做单一刚体在一静态空间的路径规划;事实上,在路径规划的过程中,降低刚体于静态空间位能的作法可视为某种程度的刚体与自由空间的形狀比对。在路径规划演算法中,刚体位置会沿着路径改变、但大小不变;然而,在形狀比对中,比对物体的位置变化不大,但其大小却会随之增 长。当比对物体增大后,如能调整其位置及姿态以降低位能,则可获得一个较好的比对形狀。此外,由于三维物体资料经常为点资讯(如range data),资料量大且不易解讀,以位能场为基础之形狀比对演算法可直接使用物体的点资讯作比对,可省去费时的物体点资讯前处理。由实验结果得知,所提出的演算法在物体之路径规划与形狀比对均有不错之成果,而后者对于部分遮蔽的物体亦可适用。 In this thesis, along the general direction of free space modeling using potential models, various applications of potential models are investigated. Variant potential-based algorithms are proposed to solve (1) path planning and (2) shape matching problems. The common idea of these algorithms is to use the repulsion exerted on an object, in forms of repulsive force and torque, from free space boundaries to achieve the best shape match between them. The object can be rigid or articulated, and the best match in shape is accomplished by adjusting object configuration, i.e., location and orientation, to minimize the potential fields among them. In the path planning algorithm of manipulators, the bewtonian potential is used to represent manipulators and obstacles with charged boundaries in a 2-D workspace. The approach computes, similar to that done in electrostatics, repulsive force and torque between charged objects in the workspace. A collision-free path of a manipulator will then be obtained by locally adjusting the manipulator configuration to search for minimum potential configurations using these force and torque. The proposed approach is efficient because these potential gradients are analytically tractable. The above potential-based path planning approach for manipulators is extended to three dimensions using the generalized potential model [1] instead of Newtonian potential. In [1], it is shown that the Newtonian potential, being harmonic in the 3-D space, can not prevent a charged point object from running into another object whose surface is uniformly charged. While the base of a manipulator is fixed, an articulated robot has higher DOF due to its moving base. A modified path planning algorithm based on the same generalized potential model is also proposed for articulated robots with moving bases in this thesis. In addition, the repulsion between an input object and a shape template is also utilized in the shape matching approach proposed in this thesis. In [2], it proposed a potential-based path planner for a single rigid robot among stationary and rigid obstacles in 3-D workspace. Indeed, the minimization of potential between robots and obstacles is a shape matching procedure of a robot within a free space in some respects. While a rigid robot moves along a path in a free space without changing its size in path planning, the object stays about the same location inside the shape template with growing size in shape matching. According to the proposed approach, a better match in shape between the template object and the input object can be obtained if the input object translates and reorients itself to reduce the potential while growing in size. Since objects are usually represented by mass and unstructured row data, e.g., range data, existed shape matching algorithms may have a preprocessing procedure to extract features from row data of objects. However, the proposed potential-based algorithm can directly perform the matching with range data of objects without preprocessing procedures. Simulation results show that the proposed algorithms work well for both path planning and shape matching applications. The latter is also practicable to objects with incomplete surface descriptions, e.g., due to a partial view. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT008623810 http://hdl.handle.net/11536/38113 |
显示于类别: | Thesis |
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