Position tracking and sensors self-calibration in autonomous mobile robots by Gauss-Newton optimization

Abstract

The design and development of the pose tracking system for an autonomous mobile robot and the time consuming calibration of its intrinsic sensor parameters (e.g., displacement, misalignment and iron distortions of an inertial measurement unit) are one of the preliminary requirements of any project involving a mobile robot platform. This paper introduces ROAMFREE, a turn-on-and-go multiple sensors pose tracking and self-calibration framework adaptable to different mobile robot platforms (e.g., Ackerman steering vehicles, quadrotor aerial vehicles, omnidirectional mobile robots). We formulate the sensor fusion problem as a Gauss-Newton optimization on an hyper-graph where nodes represent poses and calibration parameters while edges represent nonlinear measurement constraints. This formulation allows us to solve both online pose tracking and offline sensor self-calibration problems.