Try to Start It! The Challenge of Reusing Code in Robotics Research

This letter reviews the source code published with the papers of a flagship robotics research conference, 2017 International Conference on Robotics and Automation. The aim is to investigate whether the code is actually useful, i.e., can be reused by an interested reader without much effort. The interest is twofold: for one side, it makes possible to replicate and validate the results of the research; for another side, it facilitates new progress on the field, since researchers can build new systems on top of existing work. Unfortunately, reusing code is not as straightforward as it could seem, and there is a need for tools that alleviate the effort for integrating someone else's code into the own user's system. We propose the use of Docker, a Linux container technology, to turn the source code repositories into executable images, that can be run and tested locally, in an isolated environment, without the need of a costly integration with the host system

ROSLab Sharing ROS Code Interactively With Docker and JupyterLab

The success of the Robot Operating System (ROS) and the advance of open source ideas have radically changed and improved the experience of sharing software among members of the robotics community. Yet the lack of a suitable workflow for continuous integration and verification in robotics represents a significant obstacle to developing software that can be run by independent users for testing and reusing purposes

Dockerización de ROS para despliegue ágil de algoritmos de exploración

En este trabajo se presenta la utilización de contenedores para realizar pruebas con diferente algoritmos de exploración. Los mismos fueron implementados en el sistema operativo para robots ROS, y evaluados mediante el simulador Gazebo dentro del mismo contenedor. Se diseñaron simulaciones para utilizar dos algoritmos de SLAM y el algoritmo de exploración de fronteras más cercanas. También se analizan las ventajas de utilizar contenedores a la hora de realizar las pruebas. El presente trabajo fue desarrollado en ROS Kinetic Kame y simulado en Gazebo 7, los cuales se ejecutan mediante un contenedor de Docker. Se presentan los resultados obtenidos, como también un repositorio en el cual puede encontrarse el archivo Dockerfile y los algoritmos utilizados en las pruebas.Sociedad Argentina de Informática e Investigación Operativ

Dockerización de ROS para despliegue ágil de algoritmos de exploración

En este trabajo se presenta la utilización de contenedores para realizar pruebas con diferente algoritmos de exploración. Los mismos fueron implementados en el sistema operativo para robots ROS, y evaluados mediante el simulador Gazebo dentro del mismo contenedor. Se diseñaron simulaciones para utilizar dos algoritmos de SLAM y el algoritmo de exploración de fronteras más cercanas. También se analizan las ventajas de utilizar contenedores a la hora de realizar las pruebas. El presente trabajo fue desarrollado en ROS Kinetic Kame y simulado en Gazebo 7, los cuales se ejecutan mediante un contenedor de Docker. Se presentan los resultados obtenidos, como también un repositorio en el cual puede encontrarse el archivo Dockerfile y los algoritmos utilizados en las pruebas.Sociedad Argentina de Informática e Investigación Operativ

Dockerización de ROS para despliegue ágil de algoritmos de exploración

En este trabajo se presenta la utilización de contenedores para realizar pruebas con diferente algoritmos de exploración. Los mismos fueron implementados en el sistema operativo para robots ROS, y evaluados mediante el simulador Gazebo dentro del mismo contenedor. Se diseñaron simulaciones para utilizar dos algoritmos de SLAM y el algoritmo de exploración de fronteras más cercanas. También se analizan las ventajas de utilizar contenedores a la hora de realizar las pruebas. El presente trabajo fue desarrollado en ROS Kinetic Kame y simulado en Gazebo 7, los cuales se ejecutan mediante un contenedor de Docker. Se presentan los resultados obtenidos, como también un repositorio en el cual puede encontrarse el archivo Dockerfile y los algoritmos utilizados en las pruebas.Sociedad Argentina de Informática e Investigación Operativ

Infrastructure as Code Strategies and Benefits in Cloud Computing

Hybrid and multicloud infrastructure implementation without automation and versioning strategy can negatively impact organizations’ productivity. Organization leaders must ensure that infrastructures are implemented using the infrastructure as code (IaC) strategy because implementation solutions, including automated and DevOps procedures, provide assets for repeatable infrastructure implementation use cases. Grounded in the disruptive innovation theory, the purpose of this qualitative pragmatic inquiry study was to explore strategies solution architects use to implement IaC architecture using repeatable assets with DevOps procedures in cloud computing. The participants were seven solution architects in the information technology (IT) industry within the United States who have successfully implemented IaC in hybrid and multicloud within the past 3 years in cloud computing with DevOps procedures. Data were collected using semi-structured interviews, a focus group, and IT industry documents. The data analysis processes were analyzed using thematic analysis Eight themes emerged: IaC benefits, IaC cloud computing models, IaC cloud service providers, IaC configuration best practices, IaC DevOps practices, IaC implementation tools, IaC Kubernetes platforms, and IT infrastructure design practices. A specific recommendation is for organizational leaders to implement the IaC approach as it offers sustaining and disruptive innovation benefits, in addition, space agencies such as the National Aeronautics and Space Administration (NASA), European Space Agency (ESA), et al., could use this study in their mission infrastructures. The implications for positive social change include the potential to make the user application offerings affordable as it supports IT innovation in hybrid and multicloud globally

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

New approaches to the emerging social neuroscience of human-robot interaction

Prehistoric art, like the Venus of Willendorf sculpture, shows that we have always looked for ways to distil fundamental human characteristics and capture them in physically embodied representations of the self. Recently, this undertaking has gained new momentum through the introduction of robots that resemble humans in their shape and their behaviour. These social robots are envisioned to take on important roles: alleviate loneliness, support vulnerable children and serve as helpful companions for the elderly. However, to date, few commercially available social robots are living up to these expectations. Given their importance for an ever older and more socially isolated society, rigorous research at the intersection of psychology, social neuroscience and human-robot interaction is needed to determine to which extent mechanisms active during human-human interaction can be co-opted when we encounter social robots. This thesis takes an anthropocentric approach to answering the question how socially motivated we are to interact with humanoid robots. Across three empirical and one theoretical chapter, I use self-report, behavioural and neural measures relevant to the study of interactions with robots to address this question. With the Social Motivation Theory of Autism as a point of departure, the first empirical chapter (Chapter 3) investigates the relevance of interpersonal synchrony for human-robot interaction. This chapter reports a null effect: participants did not find a robot that synchronised its movement with them on a drawing task more likeable, nor were they more motivated to ask it more questions in a semi-structured interaction scenario. As this chapter heavily relies on self-report as a main outcome measure, Chapter 4 addresses this limitation by adapting an established behavioural paradigm for the study of human-robot interaction. This chapter shows that a failure to conceptually extend an effect in the field of social attentional capture calls for a different approach when seeking to adapt paradigms for HRI. Chapter 5 serves as a moment of reflection on the current state-of-the-art research at the intersection of neuroscience and human-robot interaction. Here, I argue that the future of HRI research will rely on interaction studies with mobile brain imaging systems (like functional near-infrared spectroscopy) that allow data collection during embodied encounters with social robots. However, going forward, the field should slowly and carefully move outside of the lab and into real situations with robots. As the previous chapters have established, well-known effects have to be replicated before they are implemented for robots, and before they are taken out of the lab, into real life. The final empirical chapter (Chapter 6), takes the first step of this proposed slow approach: in addition to establishing the detection rate of a mobile fNIRS system in comparison to fMRI, this chapter contributes a novel way to digitising optode positions by means of photogrammetry. In the final chapter of this thesis, I highlight the main lessons learned conducting studies with social robots. I propose an updated roadmap which takes into account the problems raised in this thesis and emphasise the importance of incorporating more open science practices going forward. Various tools that emerged out of the open science movement will be invaluable for researchers working on this exciting, interdisciplinary endeavour