Efficient and inefficient ant coverage methods

被引:94
作者
Koenig, S [1 ]
Szymanski, B
Liu, YX
机构
[1] Georgia Inst Technol, Coll Comp, Atlanta, GA 30332 USA
[2] Rensselaer Polytech Inst, Dept Comp Sci, Troy, NY 12180 USA
基金
美国国家科学基金会;
关键词
ant robots; cover time; graph coverage; lawn mowing; learning real-time A*; node counting; real-time heuristic search; surveillance; vacuum cleaning;
D O I
10.1023/A:1016665115585
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Ant robots ale simple creatures with limited sensing and computational capabilities. They have the advantage that they are easy to program and cheap to build. This makes it feasible to deploy groups of ant robots and take advantage of the resulting fault tolerance and parallelism. We study, both theoretically and in simulation, the behavior of ant robots for one-time or repeated coverage of tel-rain, as required for lawn mowing, mine sweeping, and surveillance. Ant robots cannot use conventional planning methods due to their limited sensing and computational capabilities. To overcome these limitations, we study navigation methods that are based on real-time (heuristic) search and leave markings in the terrain, similar to what real ants do. These markings can be sensed by all ant robots and allow them to cover terrain even if they do not communicate with each other except via the markings, do not have any kind of memory, do not know the terrain, cannot maintain maps of the terrain, nor plan complete paths. The ant robots do not even need to be localized, which completely eliminates solving difficult and time-consuming localization problems. We study two simple real-time search methods that differ only in how the markings ale updated. We show experimentally that both real-time search methods robustly cover terrain even if the ant robots are moved without realizing this (say, by people running into them), some ant robots fail, and some markings get destroyed. Both real-time search methods are algorithmically similar, and our experimental results indicate that their cover time is similar in some terrains. Our analysis is therefore surprising. We show that the cover time of ant robots that use one of the real-time search methods is guaranteed to be polynomial in the number of locations, whereas the cover time of ant robots that use the other real-time search method can be exponential in (the square root on the number of) locations even in simple terrains that correspond to (planar) undirected trees.
引用
收藏
页码:41 / 76
页数:36
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