摘要
巡线机器人沿电力线行走时必须探测和识别各种障碍物,同时根据障碍类型规划越障行为。文章提出了一种基于Adaboost算法的架空输电线路巡线机器人障碍物识别方法。Adaboost是一个构造准确分类器的学习方法,它把一簇弱分类器通过一定的规则结合成为一个强分类器,再把这些强分类器级联成为一个快速、准确的分类器。实验结果证明了该方法的可行性。
Power transmission line inspection robot must plan its behaviors to negotiate obstacles according to their types when it is crawling along the power transmission line. For this purpose, the paper proposes a obstacle recognition method based on Adaboost algorithm. Adaboost is a learning algorithm for constructing accurate classifiers. It can construct a strong classifier by combining a series of weak classifiers through some rules, and a fast and accurate cascaded classifier could be obtained by cascading existing strong classifiers. The result of experiments proves that the algorithm is feasible.
出处
《计算机与数字工程》
2009年第11期130-133,共4页
Computer & Digital Engineering
