Improving Human-Robot Interaction and Control Through Augmented Reality
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Overall Objectives: Purchase equipment and Software required to develop the technology; Import CT Data for viewing on an AR device; Develop the tools necessary to manipulate the data in AR. With Augmented and Virtual Reality technology becoming more common and affordable everyday, new visualization techniques need to be developed that can leverage this technology to visualize data in new and useful ways. Computed Tomography (CT) scans, are the result of a powerful X-ray machine taking multiple images of the same object. These images represent slices of the original object and have extremely high resolution. Because of the high resolution, CT scanning is often used in the medical field but is becoming increasingly predominate in diverse industrial fields as well. This is an example of a CT scan that shows an object with multiple items inside. These items are represented by different colors in gray scale to indicate different densities. This is also from the data set used for the duration of the project. The data sets usually contain hundreds of slides that looks like just like this. Visualizing these large data sets can be difficult. The general approach for this seedling was to identify the devices and software that are currently in use for data visualization and evaluate them for use in the project. After that a plan was made to convert the data into a format viewable in AR. Tools were then developed to manipulate that data. The project was a success, but there is plenty of room to advance the technology and create better visualizations.
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The technology was originally designed to assist workers using gloveboxes to document nuclear materials handling issues. The application defined in the DisrupTech process was the use of the technology to improve tracking and handling of materials in pharmacies or in pharmaceutical manufacturing. This report focuses on the use of the technology in pharmacy applications to reduce drug errors.
The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.
The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.
Emerging information technologies are reshaping the following: shifts in the knowledge and skills society values, development of new methods of teaching and learning, and changes in the characteristics of learning.
System rendering latency has been recognized by senior researchers, such as Professor Fredrick Brooks of UNC (Turing Award 1999), as a major factor limiting the realism and utility of head-referenced displays systems. Latency has been shown to reduce the user's sense of immersion within a virtual environment, disturb user interaction with virtual objects, and to contribute to motion sickness during some simulation tasks. Latency, however, is not just an issue for external display systems since finite nerve conduction rates and variation in transduction times in the human body's sensors also pose problems for latency management within the nervous system. Some of the phenomena arising from the brain's handling of sensory asynchrony due to latency will be discussed as a prelude to consideration of the effects of latency in interactive displays. The causes and consequences of the erroneous movement that appears in displays due to latency will be illustrated with examples of the user performance impact provided by several experiments. These experiments will review the generality of user sensitivity to latency when users judge either object or environment stability. Hardware and signal processing countermeasures will also be discussed. In particular the tuning of a simple extrapolative predictive filter not using a dynamic movement model will be presented. Results show that it is possible to adjust this filter so that the appearance of some latencies may be hidden without the introduction of perceptual artifacts such as overshoot. Several examples of the effects of user performance will be illustrated by three-dimensional tracking and tracing tasks executed in virtual environments. These experiments demonstrate classic phenomena known from work on manual control and show the need for very responsive systems if they are indented to support precise manipulation. The practical benefits of removing interfering latencies from interactive systems will be emphasized with some classic final examples from surgical telerobotics, and human-computer interaction.
The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.
The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.
A portable unit is for video communication to select a user name in a user name network. A transceiver wirelessly accesses a communication network through a wireless connection to a general purpose node coupled to the communication network. A user interface can receive user input to log on to a user name network through the communication network. The user name network has a plurality of user names, at least one of the plurality of user names is associated with a remote portable unit, logged on to the user name network and available for video communication.