A hybrid design for robot path planning in the presence of obstacles

R. Srikant, T. Başar, N. Ahuja
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Abstract

A method combining the tools of combinatorics and optimal control theory is presented to solve the path-planning problem. Initially, a combinatorial problem is solved to identify collision-free paths originally designed for a point object. Then the problem of moving the actual object through the safe paths for the point object is posed as an optimal control problem and is solved using a numerical technique involving finite-dimensional optimization. Some of the constraints to the optimization problem are in the form of inequalities, resulting in nondifferentiable expression when augmented with the performance index. Because of this, the R. Hooke and T.A. Jeeves method (1961), which is computationally quite prohibitive, has been adopted. To overcome this burden, at least partially, a method has been introduced whereby several variables appearing in the optimization are grouped into aggregate quantities, thus reducing the number of actual variables used in the iterations. 2-D and 3-D examples illustrate the applicability of the proposed hybrid design.<>
存在障碍物时机器人路径规划的混合设计
提出了一种结合组合学和最优控制理论的方法来解决路径规划问题。首先,解决了一个组合问题,以确定最初为点对象设计的无碰撞路径。将实际物体在安全路径上的移动问题作为最优控制问题,利用有限维优化的数值方法进行求解。优化问题的一些约束以不等式的形式存在,当与性能指标增广时,其表达式不可微。因此,采用了R. Hooke和T.A. Jeeves方法(1961),该方法在计算上是相当令人望而却步的。为了克服这个负担,至少部分地,已经引入了一种方法,将优化中出现的几个变量分组到总量中,从而减少迭代中使用的实际变量的数量。二维和三维实例说明了所提出的混合设计的适用性。
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