VINS LOCALIZATION METHOD BASED ON ADAPTIVE FUSION OF VISUAL POINT AND LINE FEATURES
Due to the low positioning accuracy of Vinsmono algorithm in weak texture environment,and the poor real-time performance of PL-vinsmono algorithm which directly introduces line features,this paper proposes a VINS positioning method based on adaptive fusion of visual point and line features.The point feature quality was evaluated at the front end,and the line feature was determined according to the point feature quality.Different loss functions were constructed on the back end for iteration,which improved the localization accuracy of the algorithm in weak texture environment and improved the real-time performance in rich texture environment.Experimental results show that the average positioning accuracy of the algorithm is 16.7％higher than that of Vinsmono algorithm in the weak texture environment,and in the rich texture environment,the average time consumption of PL-vinsmono algorithm is reduced by 41.7％.
万方数据
维普
