Robust Magnetic Field Loop Closure Detection for Low-Cost Robot’s Localization and Mapping

The robot realizes the perception of its own location through the fusion of multiple navigation sources. However, there are limits in application scenarios and cost for various navigation sources such as vision, laser, and inertial measurement unit. Therefore, a robust magnetic field loop closure detection for low-cost robot's localization and mapping method is proposed in this paper. In front-end, The MEMS inertial measurement unit and wheel odometer are fused to estimate the pose state of the robot, andmagnetic field sequence loop closure is detected in DTW algorithm, and a general graph optimization method is applied to optimize the pose in back-end. Experiments show that this method can effectively detect the magnetic sequence loop closures and eliminate the cumulative error in inertial recurrence, realize the long-time continuous indoor positioning of the robot.