Rapid Development of Manifold-Based Graph Optimization Systems for Multi-Sensor Calibration and SLAM

René Wagner; Oliver Birbach; Udo Frese

In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-11), September 25-30, San Francisco, CA, USA, Pages 3305-3312, IEEE, 2011.


Non-linear optimization on constraint graphs has recently been applied very successfully in a variety of SLAM backends. We combine this technique with a principled way of handling non-Euclidean spaces, 3D orientations in particular, based on manifolds to build a generic and very flexible framework, the Manifold Toolkit for Matlab (MTKM). We show that MTKM makes it particularly easy to solve non-trivial multi-sensor calibration problems while remaining generic enough to handle a very different class of problems, namely SLAM, as well: After an introductory example on single camera calibration we apply MTKM to calibration of stereo vision and IMU w.r.t. the kinematic chain of a service robot, RGB-D and accelerometer calibration of a Microsoft Kinect, stereo calibration on a Nao soccer robot, and several SLAM benchmark data sets illustrating MTKM’s versatility. MTKM and all presented examples will be published as open source upon acceptance of this paper1.

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz