Refine
Document Type
- Conference Proceeding (11)
- Patent (4)
- Contribution to a Periodical (3)
- Article (reviewed) (2)
Conference Type
- Konferenzartikel (10)
- Konferenz-Abstract (1)
Language
- English (13)
- German (6)
- Other language (1)
Is part of the Bibliography
- yes (20)
Keywords
- Robotics (2)
- energy harvesting (2)
- vibration harvester (2)
- 3D Printed Force Sensor (1)
- 3D bin picking (1)
- 3D printed (1)
- 3D printing (1)
- 3D-Druck von leitfähigen Materialien (1)
- Capacitive Liquid Level Sensor (1)
- Cobotik (1)
Institute
Open Access
- Open Access (7)
- Closed Access (6)
- Closed (4)
- Bronze (1)
Dieser Beitrag stellt die Möglichkeiten des 3D-Druckes unter der Berücksichtigung von Mensch-Roboter-Kollaborations-Anforderungen dar. Dabei werden die Vorteile mit besonderem Fokus auf die zusätzliche Gestaltungsfreiheit erläutert. Anhand von Beispielen wird der Stand der Technik bereits eingesetzter Sensorik sowie deren Notwendigkeit in Greifsystemen erläutert. Im weiteren Verlauf dieses Beitrags werden allgemeine Verfahren für die additive Verarbeitung von leitfähigen Materialien vorgestellt. Daran angeknüpft sind Beispiele speziell zur 3D-gedruckten Sensorik. Abgerundet wird der Beitrag mit einem Ausblick bezüglich 3D-gedruckter Sensorik in MRK-Greifsystemen.
In der Forschungsgruppe um Prof. Dr. Thomas Wendt werden Themen in unterschiedlichsten Bereichen von Automatisierungstechnik über funktionale Sicherheit bis hin zur 3D-gedruckten Elektronik / Sensorik behandelt. Insgesamt arbeiten vier Doktoranden und vier Mitarbeiter an der Weiterentwicklung der verschiedenen Technologien, die in diesem Artikel zusammengefasst dargestellt sind.
O'Barro - Cocktails 4.0
(2019)
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.
Implementation of lightweight design in the product development process of unmanned aerial vehicles
(2017)
The development and manufacturing of unmanned aerial vehicles (UAVs) require a multitude of design rules. Thereby, additive manufacturing (AM) processes provide a number of significant advantages over conventional production methods, particularly for implementing requirements with regard to lightweight construction and sustainability. A new, promising approach is presented, with which, through the combination of very light structural elements with a ribbed construction, an attached covering by means of foil is used. This contribution develops and presents a development process that is based on various development cycles. Such cycles differ in their effort and scope within the overall development, and may only comprise one part of the development process, or the entire development process. The applicability of this development process is demonstrated within the framework of a comprehensive case study. The aim is to develop an additively manufactured product that is as light as possible in the form of a UAV, along with a sustainable manufacturing process for such product. Finally, the results of this case study are analyzed with regard to the improvement of lightweight construction.
Human–robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human–machine differentiation to the speed and separation monitoring in human–robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.
Avoiding collisions between a robot arm and any obstacle in its path is essential to human-robot collaboration. Multiple systems are available that can detect obstacles in the robot's way prior and subsequent to a collision. The systems work well in different areas surrounding the robot. One area that is difficult to handle is the area that is hidden by the robot arm. This paper focuses on pick and place maneuvers, especially on obstacle detection in between the robot arm and the table that robot is located on. It introduces the use of single pixel time-of-flight sensors to detect obstacles directly from the robot arm. The proposed approach reduces the complexity of the problem by locking axes of the robot that are not needed for the pick and place movement. The comparison of simulated results and laboratory measurements show concordance.
Separation Estimation with Thermal Cameras for Separation Monitoring in Human-Robot Collaboration
(2022)
Human-Robot Collaborative applications have the drawback of being less efficient than their non-collaborative counterparts. One of the main reasons is, that the robot has to slow down when a human being is within the operating space of the robot. There are different approaches on dynamic speed and separation monitoring in human-robot collaborative applications. One approach additionally differentiates between human and non-human objects to increase efficiency in speed and separation monitoring. This paper proposes to estimate the separation distance by measuring the temperature of the approaching object. Measurements show that the measured temperature of a human being decreases with 1 deg C per meter distance from the sensor. This allows an estimation of separation between a robotic system and a human being.