Graph Optimization Approach to Range-Based Localization

In this article, we propose a general graph optimization-based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed in position graph, then the robot over sliding window is estimated by graph-based optimization algorithm. Moreover, convergence analysis algorithm provided, effects number iterations size localization accuracy analyzed. Extensive experiments quadcopter under variety scenarios verify effectiveness proposed demonstrate much higher than existing methods, especially altitude direction.