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3D Bin Picking with an innovative powder filled gripper and a torque controlled collaborative robot
(2023)
A new and innovative powder filled gripper concept will be introduced to a process to pick parts out of a box without the use of a camera system which guides the robot to the part. The gripper is a combination of an inflatable skin, and a powder inside. In the unjammed condition, the powder is soft and can adjust to the geometry of the part which will be handled. By applying a vacuum to the inflatable skin, the powder gets jammed and transforms to a solid shaped form in which the gripper was brought before applying the vacuum. This physical principle is used to pick parts. The flexible skin of the gripper adjusts to all kinds of shapes, and therefore, can be used to realize 3D bin picking. With the help of a force controlled robot, the gripper can be pushed with a consistent force on flexible positions depending of the filling level of the box. A Kuka LBR iiwa with joint torque sensors in all of its seven axis’ was used to achieve a constant contact pressure. This is the basic criteria to achieve a robust picking process.
AV delay (AVD) optimization is mandatory in cardiac resynchronization (CRT) for heart failure. Several time consuming methods exist. We initialized development of left-atrial electrogram (LAE) feature for Biotronik ICS3000 programmer. It can be utilized to approximate optimal AV delay in CRT patients with pacing systems irrespective of make and model. Using this feature, we studied the share of interatrial conduction intervals (IACT) on individual echo AVD in 45 CRT patients (34m, 11f, mean age 69±6yrs.). The percentage of IACT on optimal echo AVD resulted in44.5±22.1% for VDD and 70.7±10.9% for DDD operation. In all patients, optimal echo AVDs exceeded the individual IACT by a duration of 52.5±33.3ms (p<0.001), at mean. Therefore, if AV delay optimization is not possible or not practicable in CRT patients, AVD should be approximated by individually measuring IACT and adding about 50ms.
This work describes a camera-based method for the calibration of optical See-Through Glasses (STGs). A new calibration technique is introduced for calibrating every single display pixel of the STGs in order to overcome the disadvantages of a parametric model. A non-parametric model compared to the parametric one has the advantage that it can also map arbitrary distortions. The new generation of STGs using waveguide-based displays [5] will have higher arbitrary distortions due to the characteristics of their optics. First tests show better accuracies than in previous works. By using cameras which are placed behind the displays of the STGs, no error prone user interaction is necessary. It is shown that a high accuracy tracking device is not necessary for a good calibration. A camera mounted rigidly on the STGs is used to find the relations between the system components. Furthermore, this work elaborates on the necessity of a second subsequent calibration step which adapts the STGs to a specific user. First tests prove the theory that this subsequent step is necessary.
Flexible Three-dimensional Camera-based Reconstruction and Calibration of Tracked Instruments
(2016)
Navigated instruments commonly include applied parts, e.g. burrs or saw blades, that need to be calibrated with respect to the attached or integrated tracker. Since this calibration has to be very precise, it is often performed by the manufacturer. However, due to the great variety of instruments and the option to exchange the applied parts (e.g. burrs) there is a definite demand for flexible and generic calibration techniques. Furthermore, if we look into the medical field, there is also a need for calibrating sterile instruments. We propose a new and flexible camera-based calibration technique that addresses these demands by working contactlessly, precisely, and generically for a large variety of tracked instruments. This is realized using one or more tracked cameras which are calibrated with respect to an attached or integrated tracker. The tracked instrument is rotated in front of the camera(s) and its 3D geometry and surface are reconstructed from the 2D images in the coordinate system of the attached or integrated tracker. The 3D geometry of the navigated instrument was reconstructed with an accuracy of under 0.2 mm. The radius of a sphere-shaped instrument was reconstructed with an RMS deviation of 0.015mm.
This work describes a non-parametric camera-based method for the calibration of Optical See-Through Glasses (OSTG). Existing works model the optical system through perspective projection and parametric functions. In the border areas of the displays such models are often inadequate. Moreover, rigid calibration patterns, that produce only a small amount of non-equidistant point correspondences, are used. In order to overcome these disadvantages every single display pixel is calibrated individually. The error prone user interaction is avoided by using cameras placed behind the displays of the OSTG. The displays show a shifting pattern that is used to calculate the pixels' locations. A camera mounted rigidly on the OSTG is used to find the relations between the system components. The obtained results show better accuracies than in previous works and prove that a second calibration step for user adaptation is necessary for high accuracy applications.
Analysis of Amplitude and Phase Errors in Digital-Beamforming Radars for Automotive Applications
(2020)
Fundamentally, automotive radar sensors with Digital-Beamforming (DBF) use several transmitter and receiver antennas to measure the direction of the target. However, hardware imperfections, tolerances in the feeding lines of the antennas, coupling effects as well as temperature changes and ageing will cause amplitude and phase errors. These errors can lead to misinterpretation of the data and result in hazardous actions of the autonomous system. First, the impact of amplitude and phase errors on angular estimation is discussed and analyzed by simulations. The results are compared with the measured errors of a real radar sensor. Further, a calibration method is implemented and evaluated by measurements.
Ein neuer Ansatz wurde für mobile Roboter zur gleichzeitigen 3D (Drei-Dimensionaler) Kartierung und Lokalisierung vorgestellt. Die Grundlage bilden attributierte Flächenmodelle, die z.B. von segmentierten Laserscanner-Tiefenbildern stammen. Zur Optimierung der Gesamtähnlichkeit zwischen Flächenmodellen unter Zeitbedingungen werden mehrere Verfahren (Beschränkte Baumsuche, Iterative Verfeinerung, Evolutionäralgorithmus) kombiniert. Es wird speziell anhand der Ähnlichkeitsmaße gezeigt, wie das Wissen über die Lage stufenweise generiert und verwendet wird. Erste Messungen an realen segmentierten Tiefenbildfolgen zeigen, dass das Verfahren unbekannte übelappung, Verdeckung und Segmentierungsfehler toleriert sowie Echtzeitpotenzial besitzt.