The Semi-Supervised Support Vector Machine of Path Planning

This paper puts forward a semi-supervision support vector machine (SVM) of path planning algorithm. First, part of known identification samples were applied to give labels of unknown identification samples by using the similarity matrix, the results were sent to support vector machine process, then a path was got, through the random initial of the known obstacle identification experiments to avoid falling into extreme, this method reduces the time cost bigger compared with other algorithm.