A comparative study of sensor-based path-planning algorithms in an unknown maze
A comparative study of sensor-based path-planning algorithms in an unknown maze
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DOI：
10.1109/iros.2000.893135
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发表时间：
2000-10
期刊：
影响因子：
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通讯作者：
H. Noborio;K. Fujimura;Y. Horiuchi
中科院分区：
文献类型：
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作者：
H. Noborio;K. Fujimura;Y. Horiuchi
一般来说，一个未知的迷宫几乎没有通往目的地的无碰撞路径。因此，在经典的基于传感器的路径规划算法Bug2， Class1, Alg1， Alg2的监督下，机器人分别反复进入排除目的地和包含目的地的长局部循环和全局循环（偏离其真实路径）。例如，在Alg1和Alg2中，我们可以指出机器人总是一次进入全局循环的情况，在Bug（alter.）和Class1（alter.）中，我们可以找到机器人频繁多次加入局部循环的另一种情况。一个复杂的迷宫通常包含这样的情况，因此机器人通过一个很长的无碰撞路径到达目的地。为了克服这个问题，我们重新审视了一种算法HD-I，它的跟踪方向通过反复试验得到了充分的改变。在HD-I中，机器人几乎不会选择不适当的方向，从而降低了进入全局和局部循环的概率。
In general, an unknown maze has few collision-free paths to a destination. Therefore, a robot supervised by the classic sensor-based path-planning algorithms Bug2, Class1, Alg1, Alg2 repeatedly enters into long local and global loops excluding and including a destination (goes out of its true way), respectively. For example, in Alg1 and Alg2, we can point out a case that a robot always enters into a global loop one time, and also in Bug(alter.) and Class1(alter.), we can find another case that a robot frequently joins a local loop many times. A complicated maze usually includes such cases, and therefore a robot arrives at a destination via a very long collision-free path. To overcome this, we revisit an algorithm, HD-I, whose following direction is adequately changed by trial and error. In HD-I, a robot hardly selects an inadequate direction and consequently decreases a probability to enter into global and local loops.