Human Interaction in Multi-User Virtual Reality

In this paper we will present an immersive multiuser environment for studying joint action and social interaction. Besides the technical challenges of immersing multiple persons into a single virtual environment, additional research questions arise: Which parameters are coordinated during a joint action transportation task? In what way does the visual absence of the interaction partner affect the coordination task? What role does haptic feedback play in a transportation task? To answer these questions and to test the new experimental environment we instructed pairs of subjects to perform a classical joint action transportation task: carrying a stretcher through an obstacle course. With this behavioral experiment we demonstrated that joint action behavior (resulting from the coordination task) is a stable process. Even though visual and haptic information about the interaction partner were reduced, humans quickly compensated for the lack of information. After a short time they did not perform significantly differently from normal joint action behavior

MoPeDT: A Modular Head-Mounted Display Toolkit to Conduct Peripheral Vision Research

Peripheral vision plays a significant role in human perception and orientation. However, its relevance for human-computer interaction, especially head-mounted displays, has not been fully explored yet. In the past, a few specialized appliances were developed to display visual cues in the periphery, each designed for a single specific use case only. A multi-purpose headset to exclusively augment peripheral vision did not exist yet. We introduce MoPeDT: Modular Peripheral Display Toolkit, a freely available, flexible, reconfigurable, and extendable headset to conduct peripheral vision research. MoPeDT can be built with a 3D printer and off-the-shelf components. It features multiple spatially configurable near-eye display modules and full 3D tracking inside and outside the lab. With our system, researchers and designers may easily develop and prototype novel peripheral vision interaction and visualization techniques. We demonstrate the versatility of our headset with several possible applications for spatial awareness, balance, interaction, feedback, and notifications. We conducted a small study to evaluate the usability of the system. We found that participants were largely not irritated by the peripheral cues, but the headset's comfort could be further improved. We also evaluated our system based on established heuristics for human-computer interaction toolkits to show how MoPeDT adapts to changing requirements, lowers the entry barrier for peripheral vision research, and facilitates expressive power in the combination of modular building blocks.Comment: Accepted IEEE VR 2023 conference pape

Laboratory and Field Evaluations of the GeoAir2 Air Quality Monitor for Use in Indoor Environments

Abstract Low-cost aerosol sensors open routes to exposure assessment and air monitoring in various indoor and outdoor environments. This study evaluated the accuracy of GeoAir2—a recently developed low-cost particulate matter (PM) monitor––using two types of aerosols (salt and dust), and the effect of changes in relative humidity on its measurements in laboratory settings. For the accuracy experiments, 32 units of GeoAir2 were used, and for the humidity experiments, 3 units of GeoAir2 were used, alongside the OPC-N3 low-cost sensor and MiniWRAS reference instrument. The normal distribution of slopes between the salt and dust aerosols was compared for the accuracy experiments. In addition, the performance of GeoAir2 in indoor environments was evaluated compared to the pDR-1500 reference instrument by collocating GeoAir2 and pDR-1500 at three different homes for five days. For salt and dust aerosols smaller than 2.5 µm (PM2.5), both GeoAir2 (r = 0.96–0.99) and OPC-N3 (r = 0.98–0.99) were highly correlated with the MiniWRAS reference instrument. However, GeoAir2 was less influenced by changes in humidity than OPC-N3. While GeoAir2 reported an increase in mass concentrations ranging from 100% to 137% for low and high concentrations, an increase between 181% and 425% was observed for OPC-N3. The normal distribution of the slopes for the salt aerosols was narrower than dust aerosol, which shows closer slope similarities for salt aerosols. This study also found that GeoAir2 was highly correlated with the pDR-1500 reference instrument in indoor environments (r = 0.80–0.99). These results demonstrate potential for GeoAir2 for indoor air monitoring and exposure assessments

A teaching concept for school experiments on radioactivity using augmented reality methods

Digital media are becoming increasingly influential in society, especially among the younger generation. Therefore, an augmented reality (AR) app was developed that simulates experiments with radioactive sources. The app runs experiments on the range and penetration power of alpha, beta and gamma radiation. It assigns virtual radiation sources, shielding materials or a detector to printed image markers, and superimposes their 3D images on the camera image. Alpha, beta and gamma radiation are clearly distinguishable by choosing different visualizations. The detector displays the measured count rates. At school, the app can be used in different ways. A concept for a teaching unit in Grade 10 was developed and tested in several classes based on a prototype of the app. The learning progress from the AR experiments was examined. Furthermore, an evaluation of the app was carried out. The most recent version of the app can be found here: https://seafile.projekt.uni-hannover.de/d/dd033aaaf5df4ec18362

GeoAir—A Novel Portable, GPS-Enabled, Low-Cost Air-Pollution Sensor: Design Strategies to Facilitate Citizen Science Research and Geospatial Assessments of Personal Exposure

The rapid evolution of air sensor technologies has offered enormous opportunities for community-engaged research by enabling citizens to monitor the air quality at any time and location. However, many low-cost portable sensors do not provide sufficient accuracy or are designed only for technically capable individuals by requiring pairing with smartphone applications or other devices to view/store air quality data and collect location data. This paper describes important design considerations for portable devices to ensure effective citizen engagement and reliable data collection for the geospatial analysis of personal exposure. It proposes a new, standalone, portable air monitor, GeoAir, which integrates a particulate matter (PM) sensor, volatile organic compound (VOC) sensor, humidity and temperature sensor, LTE-M and GPS module, Wi-Fi, long-lasting battery, and display screen. The preliminary laboratory test results demonstrate that the PM sensor shows strong performance when compared to a reference instrument. The VOC sensor presents reasonable accuracy, while further assessments with other types of VOC are needed. The field deployment and geo-visualization of the field data illustrate that GeoAir collects fine-grained, georeferenced air pollution data. GeoAir can be used by all citizens regardless of their technical proficiency and is widely applicable in many fields, including environmental justice and health disparity research

Pros and Cons of Industrial Robots in Additive Manufacturing

Advances in non-planar, multi-axis, and hybrid material extrusion additive manufacturing techniques increasingly demand active nozzle orientation control. Industrial articulated robot arms are commonly implemented for repetitive manufacturing tasks and these arms are becom- ing a common choice of motion platform for additive manufacturing given their ubiquity and flexibility. Here we explore the pragmatic benefits and challenges of using industrial robotic arms for extrusion additive manufacturing. While robotic arms from established manufacturers are highly capable, recent offerings are more easily integrated and safer, while providing the same or improved capabilities as the more traditional models.Mechanical Engineerin

3D High-quality Textile Reconstruction with Synthesized Texture

3D garment model plays an important role in the fashion industry. However, not much work focus on extracting high-quality clothes from scanned data. The texture is limited by photography methods in 3D scanning. This paper proposes a novel framework of reconstructing high-quality 3D garment models with synthesized texture. Firstly, a pipeline of 3D garment processing is proposed to obtain a better 3D model based on KinectFusion. Then, DeepTextures is used to synthesize a new texture. To our best knowledge, this is the first paper combining 3D garment reconstruction and texture synthesis. Experimental results show that our method can conveniently obtain 3D garment models and realistic textures