Potential-based Path Planning and Shape Matching

• Main Author: 林建州
• Other Authors: 莊仁輝
• Format: Others
• Language: en_US
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/76335233853615552077

博士 === 國立交通大學 === 資訊科學系所 === 93 === 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.