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Dirk Kraft

7 accepted papers

2019

Rapid Estimation of Optical Properties for Simulation-Based Evaluation of Pose Estimation Performance

IROS 2019poster

A growing trend in computer vision is the use of synthetic images for the evaluation of computer vision algorithms such as 3D pose estimation. This is partly due to the availability of high-quality render engines, which provide highly realistic synthetic images. However, the realism of the rendered…

Cited by 1SourceScholar
2018

Adapting Parameterized Motions Using Iterative Learning and Online Collision Detection

ICRA 2018poster

Achieving both the flexibility and robustness required to advance the use of robotics in small and medium-sized productions is an essential but difficult task. A fundamental problem is making the robot run blindly without additional sensors while still being robust to uncertainties and variations in…

Cited by 3SourceScholar
2018

BOP: Benchmark for 6D Object Pose Estimation

ECCV 2018poster

We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: i) eight datasets in a unified format that cover different practical…

2018

Optimisation of Trap Design for Vibratory Bowl Feeders

ICRA 2018poster

Vibratory bowl feeders (VBFs) are a widely used option for industrial part feeding, but their design is still largely manual. A subtask of VBF design is determining an optimal parameter set for the passive devices, called traps, which the VBF uses to ensure correct part orientation. This paper propo…

Cited by 21SourceScholar
2018

Optimizing Sensor Placement: A Mixture Model Framework Using Stable Poses and Sparsely Precomputed Pose Uncertainty Predictions

IROS 2018poster

In many robotics tasks successful execution requires high precision pose estimates of the objects in the workcell. When the object pose is provided by a computer vision system it is therefore crucial that the vision system is configured such that the required precision is achieved. An important part…

Cited by 6SourceScholar
2017

Prediction of ICP pose uncertainties using Monte Carlo simulation with synthetic depth images

IROS 2017poster

In robotics, vision sensors are used to estimate the poses of objects in the environment. However, it is a fundamental problem that the estimated poses are not always accurate enough for a given robotic task. Proper sensor placement can mitigate this problem. We present a method which can predict th…

Cited by 35SourceScholar
2017

Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition

ICCV 2017poster

It is possible to associate a highly constrained subset of relative 6 DoF poses between two 3D shapes, as long as the local surface orientation, the normal vector, is available at every surface point. Local shape features can be used to find putative point correspondences between the models due to t…

Cited by 83PDFScholar