Visual feedback for humans about robots' perception in collaborative environments

During the last years, major advances on artificial intelligence have successfully allowed robots to perceive their environment, which not only includes static but also dynamic objects such as humans. Indeed, robotic perception is a fundamental feature to achieve safe robots' autonomy in human-robot collaboration. However, in order to have true collaboration, both robots and humans should perceive each other’s intentions and interpret which actions they are performing. In this work, we developed a visual representation tool that illustrates the robot's perception of the space that is shared with a person. Specifically, we adapted an existent system to estimate the human pose, and we created a visualisation tool to represent the robot's perception about the human-robot closeness. We also performed a first evaluation of the system working in realistic conditions using the Tiago robot and a person as a test subject. This work is a first step towards allowing humans to have a better understanding about robots' perception in collaborative scenarios.Peer ReviewedPreprin

DiME and AGVIS A Distributed Messaging Environment and Geographical Visualizer for Large-scale Power System Simulation

This paper introduces the messaging environment and the geographical visualization tool of the CURENT Large-scale Testbed (LTB) that can be used for large-scale power system closed-loop simulation. First, Distributed Messaging Environment (DiME) implements an asynchronous shared workspace to enable high-concurrent data exchange. Second, Another Grid Visualizer (AGVis) is presented as a geovisualization tool that facilitates the visualization of real-time power system simulation. Third, case studies show the use of DiME and AGVis. The results demonstrate that, with the modular structure, the LTB is capable of not only federal use for real-time, large-scale power system simulation, but also independent use for customized power system research.Comment: 5 pages, 7 figures, conferenc

CodeBase Relationship Visualizer: Visualizing Relationships Between Source Code Files

Understanding relationships between files and their directory structure is a fundamental part of the software development process. However, it can be hard to grasp these relationships without a convenient way to visualize how files are connected and how they fit into the directory structure of the codebase. In this paper we describe CodeBase Relationship Visualizer (CBRV), a Visual Studio Code extension that interactively visualizes the relationships between files. CBRV displays the relationships between files as arrows superimposed over a diagram of the codebase\u27s directory structure. CBRV comes bundled with visualizations of the stack trace path, a dependency graph for Python codebases, and a hyperlink graph for HTML and Markdown. CBRV also exposes an API that can be used to create visualizations for multiple different relationships. CBRV is a convenient and easy-to-use tool that offers a big picture perspective on the relationships within a codebase

Iris: an Extensible Application for Building and Analyzing Spectral Energy Distributions

Iris is an extensible application that provides astronomers with a user-friendly interface capable of ingesting broad-band data from many different sources in order to build, explore, and model spectral energy distributions (SEDs). Iris takes advantage of the standards defined by the International Virtual Observatory Alliance, but hides the technicalities of such standards by implementing different layers of abstraction on top of them. Such intermediate layers provide hooks that users and developers can exploit in order to extend the capabilities provided by Iris. For instance, custom Python models can be combined in arbitrary ways with the Iris built-in models or with other custom functions. As such, Iris offers a platform for the development and integration of SED data, services, and applications, either from the user's system or from the web. In this paper we describe the built-in features provided by Iris for building and analyzing SEDs. We also explore in some detail the Iris framework and software development kit, showing how astronomers and software developers can plug their code into an integrated SED analysis environment.Comment: 18 pages, 8 figures, accepted for publication in Astronomy & Computin

Algorithms for a multi-projector CAVE system

With regards to facilitating development of VR applications, the main pur- pose of ALIVE is to reduce the amount of attention that the application developer has to dedicate to the issues that were described previously. In this project we aim to abstract the user from dealing with: Input devices. Display number and layout. De nition of the virtual cameras. Synchronization issues between cluster nodes. Notably missing from the list are 3D sound rendering and synchroniza- tion for non-deterministic algorithms. These problems are out of the scope of this project and will be addressed in the future. Summarizing the objectives of this project, we list: Provide an abstraction API, that facilitates development and deploy- ment of VR applications. Create a polygon renderer application based on the proposed API

HierarchyMap: A Novel Approach to Treemap Visualization of Hierarchical Data

The HierarchyMap describes a novel approach for Treemap Visualization method for representing large volume of hierarchical information on a 2-dimensional space. HierarchyMap algorithm is a new ordered treemap algorithm. Results of the implementation of HierarchyMap treemap algorithm show that it is capable of representing several thousands of hierarchical data on 2-dimensional space on a computer and Portable Device Application (PDA) screens while still maintaining the qualities found in existing treemap algorithms such as readability, low aspect ratio, reduced run time, and reduced number of thin rectangles. The HierarchyMap treemap algorithm is implemented in Java programming language and tested with dataset of Departmental and Faculty systems of Universities, Family trees, Plant and Animal taxonomy structure

ARIADNEplus Data Aggregation Pipeline:User Guide (2.4)

The purpose of this User Guide is to provide a short introduction to the ARIADNEplus data aggregation pipeline. It defines, for the archaeological data providers, the process by which their data should be uploaded to the ARIADNE Content Cloud, so that it appears in the ARIADNEplus Catalogue, and can be searched via the ARIADNEplus Portal