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The coverage path planning algorithm is indispensable to intelligent mobile machines, such as demining robots, autonomous underwater vehicles, plant protection UAVs, automatic painting robots, cleaning robots and some other applications, involving many areas like military, agriculture, manufacturing and civilian, so the algorithm has rich value on scientific research and business market. In this article, a variety of current mainstream coverage path planning algorithms are described. Based on the working environment information is known or not, coverage path planning algorithms are divided into two types of “off-line” and “on-line”. This article introduces off-line algorithms such as trapezoidal decomposition, boustrophedon cellular decomposition, line-sweep-based decomposition method, grid method of known spaces and quad-tree method, on-line algorithms such as neural network-based coverage, grid-based coverage using spanning trees and so on. This article also analyses and compares coverage completeness, efficiency, energy costs and achievement difficulty of each coverage path planning algorithm, advantages and pitfalls of each algorithm are pointed out. The technology development trends of coverage path planning algorithm for intelligent machinery are given in this article, multi-intelligent fusion algorithm can compensate for deficiencies of single-intelligent one, and it will be the future trend.