A number of existing maze-searching and robot motion planning algorithms are studied from the standpoint of a single performance criterion. The main motivation is to build a framework for selecting basic planning algorithms for autonomous vehicles and robot arm manipulators that operate in an environment filled with unknown obstacles of arbitrary shapes. In choosing an appropriate criterion, it is noted that besides convergence, minimizing the length of generated paths is a single major consideration in planning algorithms. In addition, since no complete information is ever available, optimal solutions are ruled out. Accordingly, the performance criterion is defined in terms of the upper bound on the length of generated paths as a function of the maze perimeter. The comparison shows that the special structure of graphs that correspond to planar environments with obstacles actually makes it possible to exceed the efficiency of general maze-searching algorithms.
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