Simultaneous calibration, localization, and mapping

The calibration parameters of a mobile robot play a substantial role in navigation tasks. Often these parameters are subject to variations that depend either on environmental changes or on the wear of the devices. In this paper, we propose an approach to simultaneously estimate a map of the environment, the position of the on-board sensors of the robot, and its kinematic parameters. Our method requires no prior knowledge about the environment and relies only on a rough initial guess of the platform parameters. The proposed approach performs on-line estimation of the parameters and it is able to adapt to non-stationary changes of the configuration. We tested our approach in simulated environments and on a wide range of real world data using different types of robotic platforms.

Authors

• Rainer Kümmerle
• Giorgio Grisetti
• Wolfram Burgard

Keywords

• Mobile robots
• Robot kinematics
• Wheels
• Calibration
• Robot sensing systems
• Simultaneous Mapping
• Simultaneous Calibration
• Real-world Data
• Sensor Locations
• Mobile Robot
• Kinematic Parameters
• Environment Map
• Simulation Experiments
• Error Function
• Fisher Information
• Sum Of Terms
• Levenberg-Marquardt Algorithm
• Coordinate Frame
• Cholesky Decomposition
• Position Of The Robot
• Current Node
• Simultaneous Localization And Mapping
• Laser Ranging
• non-Euclidean
• Hypergraph
• Floor Type
• Laser Position
• Wheel Velocity
• Record Dataset
• Normal Configuration
• Parameters Of The Robot
• Robot Trajectory
• Robot Motion
• Velocity Measurements
• Loop Closure