本文为James Ng的博士论文，共203页。

本文研究了未知二维环境下的机器人导航算法，旨在提高其算法性能。执行此类导航的算法称为Bug算法。在Eyesim机器人仿真系统上实现了现有算法，并对其性能进行了测试和分析，特别是在保证终止的方法方面，探讨了Bug家族的相似性和不同之处。在现有的文献中，有七种方法用于保证终止，构成了新的Bug算法的基础：OneBug、MultiBug、LeaveBug、Bug1+和SensorBug。

本文提出了一种新的方法，该方法将离开点限制在凸形障碍物的顶点上。SensorBug是一种新算法，设计用于距离传感器，并考虑三个性能标准：数据采集频率、扫描量和路径长度。SensorBug减少了收集可见环境数据的频率，并减少了每次收集数据时的扫描量。研究结果表明，虽然降低了成本，但在任何环境下都能保证正确的终止。Curv1是一种机器人导航算法，用于在未知环境中利用一条非自相交的单一导轨引导机器人到达目标。通过一种中间算法Curv2，Curv1被扩展为一种新的算法Curv3，Curv3能够匹配多个起点和目标，并能处理自相交轨迹。

This thesis investigates robot navigationalgorithms in unknown 2 dimensional environments with the aim of improvingperformance. The algorithms which perform such navigation are called BugAlgorithms [1,30,62]. Existing algorithms are implemented on a robot simulationsystem called EyeSim [7] and their performances are measured and analyzed.Similarities and differences in the Bug Family are explored particularly inrelation to the methods used to guarantee termination. Seven methods used toguarantee termination in the existing literature are noted and form the basisof the new Bug algorithms: OneBug, MultiBug, LeaveBug, Bug1+ and SensorBug. Anew method is created which restricts the leave points to vertices of convexobstacles. SensorBug is a new algorithm designed to use range sensors and withthree performance criteria in mind: data gathering frequency, amount ofscanning and path length. SensorBug reduces the frequency at which data aboutthe visible environment is gathered and the amount of scanning for each timedata is gathered. It is shown that despite the reductions, correct terminationis still guaranteed for any environment. Curv1 [19], a robot navigationalgorithm, was developed to guide a robot to the target in an unknownenvironment with a single non-self intersecting guide track. Via anintermediate algorithm Curv2, Curv1 is expanded into a new algorithm, Curv3.Curv3 is capable of pairing multiple start and targets and coping withself-intersecting track.

1 引言与文献回顾

2 Bug导航算法的性能比较

3 Bug算法终止分析

4 在具有单个半凸障碍环境中的Bug算法性能

5 具有导轨的机器人导航

6 SensorBug：一种未知环境中基于本地距离参数的导航算法

7 总结、重要贡献与未来研究展望

附录 在Eyesim系统中实现Bug算法

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