Klaus H. Strobl

Optimal Hand-Eye Calibration

This paper presents a calibration method for eye-in-hand systems in order to estimate the hand-eye and the robot-world transformations. The estimation takes place in terms of a parametrization of a stochastic model. In order to perform optimally, a metric on the group of the rigid transformations SE(3) and the corresponding error model are proposed for nonlinear optimization. This novel metric works well with both common formulations AX=XB and AX=ZB, and makes use of them in accordance with the nature of the problem. The metric also adapts itself to the system precision characteristics. The method is compared in performance to earlier approaches

The 3D-Modeller: A Multi-Purpose Vision Platform

This paper deals with the concept and implementation of a multi-purpose vision platform. In robotics, numerous applications require perception. A multi-purpose vision platform suited for object recognition, cultural heritage preservation and visual servoing at the same time is missing. In this work, we draw attention to the design principles for such a vision platform. We present its implementation, the 3D-modeller. In specifying and combining multiple sensors, laser-range scanner, laser-stripe profiler and stereo vision, we derive the required mechanical and electrical hardware design. The concepts for synchronization and communication round offs our approach. Precision and frame rate are presented. We illustrate the versatility of the 3D-modeller by addressing four applications: 3D-modeling, exploration, tracking and object recognition. Due to its low weight and generic mechanical interface, it can be mounted on industrial robots, humanoids, or free-handed as well. The 3D-modeller is flexibly applicable, not only in research but also in industry, especially in small batch assembly.

The DLR multisensory Hand-Guided Device: the Laser Stripe Profiler

This paper presents the DLR Laser Stripe Profiler as a component of the DLR multisensory Hand-Guided Device for 3D modeling. After modeling the reconstruction process, we propose a novel method for laser plane self-calibration based on the assessment of the deformations the miscalibration leads to. In addition, the requirement for absence of optical filtering implies the development of a robust stripe segmentation algorithm. Experiments demonstrate the validity and applicability of the approaches.

More accurate pinhole camera calibration with imperfect planar target

This paper presents a novel approach to camera calibration that improves final accuracy with respect to standard methods using precision planar targets, even if now inaccurate, unmeasured, roughly planar targets can be used. The work builds on a recent trend in camera calibration, namely concurrent optimization of scene structure together with the intrinsic camera parameters [4, 8, 1]. A novel formulation is presented that allows maximum likelihood estimation in the case of inaccurate targets, as it extends the camera extrinsic parameters into a tight parametrization of the whole scene structure. It furthermore observes the special characteristics of multi-view perspective projection of planar targets. Its natural extensions to stereo camera calibration and hand-eye calibration are also presented. Experiments demonstrate improvements in the parametrization of the camera model as well as in eventual stereo reconstruction.

The self-referenced DLR 3D-modeler

In the context of 3-D scene modeling, this work aims at the accurate estimation of the pose of a close-range 3-D modeling device, in real-time and passively from its own images. This novel development makes it possible to abandon using inconvenient, expensive external positioning systems. The approach comprises an ego-motion algorithm tracking natural, distinctive features, concurrently with customary 3-D modeling of the scene. The use of stereo vision, an inertial measurement unit, and robust cost functions for pose estimation further increases performance. Demonstrations and abundant video material validate the approach.

More accurate camera and hand-eye calibrations with unknown grid pattern dimensions

This paper presents two novel approaches for accurate intrinsic and extrinsic camera calibration. The rationale behind them is the widespread violation of the traditional assumption that the metric structure of the calibration object is perfectly known. A novel formulation parameterizes a checkerboard calibration pattern in such a way that the calibration performs optimally irrespective of its actual dimensions. Simulations and experiments show that it is very rare for traditional calibration methods to come by the accuracy readily attained by this approach.

Perception errors in vision guided walking: analysis, modeling, and filtering

This article deals with specific aspects concerning the visual perception process of a humanoid walking machine. An active vision system provides the information about the environment necessary for autonomous goal-oriented locomotion. Due to errors in each stage of the perception process, ideal environment reconstruction is not possible. By modeling these errors, stochastic components can be compensated using a hybrid extended Kalman filter approach with an alternating reference frame, thus reflecting the discontinuous character of biped walking.. The perception results improved by filtering can be used for the autonomous locomotion of the robot. Experiments with the walking machine BARt-UH demonstrate the validity of our approach.

Efficient camera-based pose estimation for real-time applications

Accurate online localization is crucial for mobile robotics. In this paper, we describe a real-time image-based localization technique, which is based on a single calibrated camera. This can be supported by a second camera to improve accuracy and to provide the correct translational scale. Our goal is a robust and unbiased pose estimation in highly dynamic scenes on resource-limited systems. The presented approach is characterized through significantly improved robustness of the pose estimation, a novel approach for stereo subpixel accurate landmark initialization, and the speed-up of conventional tracking routines to achieve online capability. Although the algorithm is designed for accurate, online short-range egomotion estimation in hand-held scanning devices, it can be used for any mobile robot application as shown in this paper. Various tests and experimental results with a mobile platform and a hand-held 3D modeler are presented and discussed.

Path-dependent gaze control for obstacle avoidance in vision guided humanoid walking

This article presents a novel gaze control strategy for obstacle avoidance in the context of vision guided humanoid walking. The generic strategy is based on the maximization of the predicted visual information. For information/uncertainty management a new hybrid formulation of an extended Kalman filter is employed. The performance resulting from this view direction control scheme shows the dependence of the intelligent gazing behavior on the pre-planned local path.

Stepwise calibration of focused plenoptic cameras

A novel method for the calibration of focused plenoptic monocular cameras is proposed.In this way, the camera will deliver metric depth information instead of disparities.We detach the intrinsic camera parameters related to either brightness or depth data.We present novel initialization methods for all parameters.The accuracy is demonstrated on independent ground-truth validation data. Display Omitted Monocular plenoptic cameras are slightly modified, off-the-shelf cameras that have novel capabilities as they allow for truly passive, high-resolution range sensing through a single camera lens. Commercial plenoptic cameras, however, are presently delivering range data in non-metric units, which is a barrier to novel applications e.g. in the realm of robotics. In this work we revisit the calibration of focused plenoptic cameras and bring forward a novel approach that leverages traditional methods for camera calibration in order to deskill the calibration procedure and to increase accuracy. First, we detach the estimation of parameters related to either brightness images or depth data. Second, we present novel initialization methods for the parameters of the thin lens camera model-the only information required for calibration is now the size of the pixel element and the geometry of the calibration plate. The accuracy of the calibration results corroborates our belief that monocular plenoptic imaging is a disruptive technology that is capable of conquering new markets as well as traditional imaging domains.