WLRI - Work-Life Robotics Institute
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This contribution introduces a guideline for the fabrication of fully 3D-printed torque sensor elements. Recent advances in 3D printing technology have made it possible to produce objects and functional structures by employing a variety of 3D printing processes and materials. 3D printing therefore provides an alternative approach to sensor fabrication. Fully 3D-printed resistive torque sensors, encompassing both the elastic structure and strain gauges produced by 3D printing processes, are rarely encountered in the literature. Here, we address this gap by presenting a guideline for the fabrication of fully 3D-printed torque sensor elements. The application of the guideline is demonstrated through a prototype. The guideline consists of three main steps: ”Design”, ”Fabrication” and ”Evaluation”. As part of the guideline, the combination of different 3D printing materials and 3D printing processes will be demonstrated. In order to coordinate the different printing processes and materials, an iterative process is introduced in the design phase. In the second step, ”Fabrication”, the capabilities of a five-axis 3D printing system are demonstrated. In the final step, ”Evaluation”, the sensor element is calibrated. The aim of this guideline is to provide an orientation for the future development and research of 3D-printed sensor elements.
In this contribution, we present different ways to simplify a simulation model of an additively manufactured force sensor in the field of robot gripping technology for efficient determination of results using COMSOL Multiphysics. The results of different computational approaches are compared with the required computing time and memory requirements. A simplified analytical approach is also presented as an alternative and to verify the plausibility of the simulations.
Plastic welding is essential to fabricate process tanks in the field of semiconductor industries. Applying robot-assisted welding processes requires defining welding paths. Utilizing CAD/CAM or teach-in is both timeconsuming. In this contribution, we describe and discuss two approaches to automatically measure and extract welding paths with the robot. These approaches enable a flexible detection of welding-paths for automated plastic welding of cuboid containers.
This article demonstrates how four distinct technologies converge to create a new design for articulated robotic arms. Each technology has proven its robustness, processability, and use cases. Generative design is a common approach in mechanical engineering, while additive manufacturing is proven and accepted, even in military applications. Printable conductive materials are used in PCBs and electronics, and wireless technology is indispensable and ubiquitous. A key challenge is that these technologies can interfere with each other. For example, in 3D printing with Fused Filament Fabrication, the curing temperature of conductive ink must be compatible with the plastic's welding temperature. Conductive traces must not interfere with the wireless technology's wavelength to ensure proper function. These factors must be considered in generative design or when using AI in design phases. Despite the challenges, initial tests show promising results. This approach allows for custom-made robotic arms, reduces weight and cabling, and provides flexibility in production processes and materials, paving the way for new robotic applications.
This article provides insights into the feasibility study of the IP500® standard for use in robotics applications, specifically with the intent to utilize the CNX 200 module. The CNX 200 is a true dual-band module that enables a robust, reliable, and stable wireless connection. An articulated robot arm with six joints, designed using AI-based generative techniques, will serve as the reference product. Given that the robot is designed through generative methods, it is crucial to minimize any cabling. Therefore, the primary objective is to maintain only the power connections for the drivers, ensuring that all other communications and signals are transmitted via the wireless connection.
This research involved the design of a passive vibration harvester utilized as a sensor for measuring the frequency of periodic vibrations. The oscillator design is aligned to a specific frequency and uses the eigenfrequencies of the material and geometry. Combined with a piezoelectric structure, energy conversion sufficient for signal generation occurs only at resonance. This creates an active sensor system that does not need an external energy supply for signal generation.
This research presents a capacitive displacement sensor concept for use in a pin array gripper. The sensor measures the displacement of individual pins with a plate capacitor structure. The pin is movably positioned between the electrodes. The capacitive displacement sensor is constructed with sensing, guiding, and shielding electrodes. A homogeneous electric field is achieved between the capacitor plates to ensure a linear change in capacitance. A shielding concept for the sensor has been evaluated to minimize external interference and mutual interference between the individual displacement transducers. This ensures stable operation and reliable displacement measurements of the individual pins. The design of the concept for additive manufacturing offers advantages in terms of customization and implementation on different pin gripping systems, as well as a compact design. A test sensor was additive manufactured. The newly developed sensor was tested in an experimental setup to ensure functionality and comparing the sensory behavior with the simulations.
This work presents an extension for a coffee-machine that is intended to facilitate its use by people with disabilities. For this purpose, a control method was developed using three wireless buttons and a user interface that allows the selection of several coffee specialties. This selection is translated by a Python script into stepper motor movements fixed to the coffee-machine. With this setup, it is possible to incorporate multiple input modalities such as eye tracking and voice control.
Robotics offers new solutions for digital customer interaction. Social robots can be used in applications such as customer support, guiding people to a location on company premises, or entertainment and education. An emerging area of research is the application in community facilities for people with disabilities. Such facilities face a shortage of skilled workers that could be addressed by robotics. In this work, the application of social and collaborative robots in care facilities and workshops for the disabled is presented by providing a requirements analysis. The use of the humanoid robot Pepper in assisted living was tested and subsequently evaluated in interviews with caregivers who initiated and observed the interaction between the group and the robot. Additionally, robotic applications in assisted work were assessed, resulting in a divergence from the industrial use of robots. A comparative overview with recent literature is presented. The connection between the community home and the workshop raised the question of whether the use of different robots in both places could lead to conflicts.
Human-machine interaction can be supported by the detection of humans through the simultaneous localization and distinction from non-human objects. This paper compares modern object detection algorithms (Damo-YOLO, YOLOv6, YOLOv7 and YOLOv8) in combination with Transfer Learning and Super Resolution in different scenarios to achieve human detection on low resolution infrared images. The data set created for this purpose includes images of an empty room, images of warm coffee cups, and images of people in various scenarios and at distances ranging from two to six meters. The Average Precision AP@50 and AP@50:95 values achieved across all scenarios reach up to 98.02 % and 66.99 % respectively.