A developer needs to map those concepts to exact source code locations within the project in order to implement the requested change. Each of those requests is generally written using natural language texts, and it involves one or more domain related concepts. View full-textÄuring maintenance, software developers deal with a number of software change requests. The experimental results using real world datasets show that the proposed pruning algorithm can effectively reduce the size of the graph while maintaining the map accuracy. We propose a measure derived from Kullbach-Leibler divergence to decide whether a frame should be discarded, achieving an online implementation of the graph pruning algorithm for feature mapping, of which the pruned frame can be any of the preserved frames. However, these approaches cannot discard the already preserved frames when the robot re-visits the previously explored area. from the previous one or not informative enough. Conventionally, the size of the graph is kept small by discarding the current frame if it is not spatially far enough. The size of the graph exerts an important influence on the efficiency of the graph optimization. In pose feature graph simultaneous localization and mapping, the robot poses and feature positions are treated as graph nodes and the odometry and observations are treated as edges.
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