RobotAR: An Augmented Reality Compatible Teleconsulting Robotics Toolkit for Augmented Makerspace Experiences
More Like this
-
null (Ed.)Neural Machine Translation (NMT) performs training of a neural network employing an encoder-decoder architecture. However, the quality of the neural-based translations predominantly depends on the availability of a large amount of bilingual training dataset. In this paper, we explore the performance of translations predicted by attention-based NMT systems for Spanish to Persian low-resource language pairs. We analyze the errors of NMT systems that occur in the Persian language and provide an in-depth comparison of the performance of the system based on variations in sentence length and size of the training dataset. We evaluate our translation results using BLEU and human evaluation measures based on the adequacy, fluency, and overall rating.more » « less
-
Although Augmented Reality (AR) can be easily implemented with most smartphones and tablets today, the investigation of distance perception with these types of devices has been limited. In this paper, we question whether the distance of a virtual human, e.g., avatar, seen through a smartphone or tablet display is perceived accurately. We also investigate, due to the Covid-19 pandemic and increased sensitivity to distances to others, whether a coughing avatar that either does or does not have a mask on affects distance estimates compared to a static avatar. We performed an experiment in which all participants estimated the distances to avatars that were either static or coughing, with and without masks on. Avatars were placed at a range of distances that would be typical for interaction, i.e., action space. Data on judgments of distance to the varying avatars was collected in a distributed manner by deploying an app for smartphones. Results showed that participants were fairly accurate in estimating the distance to all avatars, regardless of coughing condition or mask condition. Such findings suggest that mobile AR applications can be used to obtain accurate estimations of distances to virtual others "in the wild," which is promising for using AR for simulations and training applications that require precise distance estimates.more » « less
-
Abstract In‐field visual inspections have inherent challenges associated with humans such as low accuracy, excessive cost and time, and safety. To overcome these barriers, researchers and industry leaders have developed image‐based methods for automatic structural crack detection. More recently, researchers have proposed using augmented reality (AR) to interface human visual inspection with automatic image‐based crack detection. However, to date, AR crack detection is limited because: (1) it is not available in real time and (2) it requires an external processing device. This paper describes a new AR methodology that addresses both problems enabling a standalone real‐time crack detection system for field inspection. A Canny algorithm is transformed into the single‐dimensional mathematical environment of the AR headset digital platform. Then, the algorithm is simplified based on the limited headset processing capacity toward lower processing time. The test of the AR crack‐detection method eliminates AR image‐processing dependence on external processors and has practical real‐time image‐processing.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3411764.3445726
