Flymation: Interactive Animation for Flying Robots

Trajectory visualization and animation play critical roles in robotics research. However, existing data visualization and animation tools often lack flexibility, scalability, and versatility, resulting in limited capability to fully explore and analyze flight data. To address this limitation, we introduce Flymation, a new flight trajectory visualization and animation tool. Built on the Unity3D engine, Flymation is an intuitive and interactive tool that allows users to visualize and analyze flight data in real time. Users can import data from various sources, including flight simulators and real-world data, and create customized visualizations with high-quality rendering. With Flymation, users can choose between trajectory snapshot and animation; both provide valuable insights into the behavior of the underlying autonomous system. Flymation represents an exciting step toward visualizing and interacting with large-scale data in robotics research.Comment: This work was presented at Workshop at ICRA 2023 ( The Role of Robotics Simulators for Unmanned Aerial Vehicles

Establishing a Framework for the development of Multimodal Virtual Reality Interfaces with Applicability in Education and Clinical Practice

The development of Virtual Reality (VR) and Augmented Reality (AR) content with multiple sources of both input and output has led to countless contributions in a great many number of fields, among which medicine and education. Nevertheless, the actual process of integrating the existing VR/AR media and subsequently setting it to purpose is yet a highly scattered and esoteric undertaking. Moreover, seldom do the architectures that derive from such ventures comprise haptic feedback in their implementation, which in turn deprives users from relying on one of the paramount aspects of human interaction, their sense of touch. Determined to circumvent these issues, the present dissertation proposes a centralized albeit modularized framework that thus enables the conception of multimodal VR/AR applications in a novel and straightforward manner. In order to accomplish this, the aforesaid framework makes use of a stereoscopic VR Head Mounted Display (HMD) from Oculus Rift©, a hand tracking controller from Leap Motion©, a custom-made VR mount that allows for the assemblage of the two preceding peripherals and a wearable device of our own design. The latter is a glove that encompasses two core modules in its innings, one that is able to convey haptic feedback to its wearer and another that deals with the non-intrusive acquisition, processing and registering of his/her Electrocardiogram (ECG), Electromyogram (EMG) and Electrodermal Activity (EDA). The software elements of the aforementioned features were all interfaced through Unity3D©, a powerful game engine whose popularity in academic and scientific endeavors is evermore increasing. Upon completion of our system, it was time to substantiate our initial claim with thoroughly developed experiences that would attest to its worth. With this premise in mind, we devised a comprehensive repository of interfaces, amid which three merit special consideration: Brain Connectivity Leap (BCL), Ode to Passive Haptic Learning (PHL) and a Surgical Simulator

Robot-Assisted Crowd Evacuation under Emergency Situations: A Survey

In the case of emergency situations, robotic systems can play a key role and save human lives in recovery and evacuation operations. To realize such a potential, we have to address many scientific and technical challenges encountered during robotic search and rescue missions. This paper reviews current state-of-the-art robotic technologies that have been deployed in the simulation of crowd evacuation, including both macroscopic and microscopic models used in simulating a crowd. Existing work on crowd simulation is analyzed and the robots used in crowd evacuation are introduced. Finally, the paper demonstrates how autonomous robots could be effectively deployed in disaster evacuation, as well as search and rescue missions

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

A standardised and cost-effective VR approach for powered wheelchair training

Mastering wheelchair driving skills is essential for the safety of wheelchair users (WUs), yet the acquisition of these skills can be challenging, and training resources can be costly or not available. Technologies such as virtual reality (VR) have grown in popularity as they can provide a motivating training environment without the risks found in real-life training. However, these approaches often deploy navigation controllers which are different from the ones WUs utilise, and do not use a standardised approach in assessing the acquisition of skills. We propose a VR training system based on the wheelchair skills training program (WSTP) and utilizing a sensor device that can be retrofitted to any joystick and communicates wirelessly with a Head-Mounted Display. In this paper, we present a first-validation study with fourteen able-bodied participants, split between a VR test group and a non-VR control group. To determine the acquisition of skills, participants complete tasks in real-life before and after the VR training, where completion time and length of joystick movements are measured. We also assess our system using heart rate measurements, the WSTP questionnaire, the simulator sickness questionnaire and the igroup presence questionnaire. We found that the VR training facilitates the acquisition of skills for more challenging tasks; thus, our system has the potential of being used for training skills of powered wheelchair users, with the benefit of conducting the training in safely and in a low-cost setup

Entorno virtual para el estudio de señales EMG

En este proyecto se amplía el sistema de simulación en Unity3D realizado para la mano robótica Allegro a la mano Shadow. Además se añade la posibilidad de poder cargar las manos con textura realista. Permite el control de la mano Shadow de manera remota mediante el nodo de ROS correspondiente. Se integra también con un módulo de adquisición de señales que pasa la información a los nodos usando ROS mediante Matlab. Para el control de la simulación mediante señales EMG, se definen unos comandos de control en el entorno de simulación que pueden ser utilizados desde dichas señales o por el usuario desde la interfaz. El sistema posibilita el control de dos manos de manera simultánea y en el caso de la mano Allegro con un control colaborativo. Como resultado se ha obtenido un sistema intuitivo. Con respecto a la conexión con las manos, el sistema tiene una buena tasa de actualización en los sistemas Allegro. En el caso de la Shadow el retardo se incrementa debido al uso del planificador, siendo mayor este retardo el sistema simulado que en el real

Co-simulation digital twin framework for testing future advanced air mobility concepts: a study with BlueSky and AirSim

The UK Future Flight Vision and Roadmap outlines the anticipated development of aviation in the UK by 2030. As part of the Future Flight demonstration segment, project HADO (High-intensity Autonomous Drone Operations) will develop, test, and deploy fully automated unmanned aircraft system (UAS) operations at London Heathrow Airport. Cranfield University is leading the synthetic test environment development within the HADO project, and a digital twin (DT) prototype was developed to enable mixed-reality tests for autonomous UAS operations. This paper enhances the existing DT by introducing new co-simulation capacities. Specifically, a co-simulation DT framework for autonomous UAS operations is proposed and tested through a demonstrative use case based on BlueSky and AirSim. This prototype integrates the traffic simulation capabilities of BlueSky with the 3D simulation capabilities of Airsim, to efficiently enhance the simulation capacities of the DT. Notably, the co-simulation framework can leverage the 3D visualization modules, UAS dynamics, and sensor models within external simulation tools to support a more realistic and high-fidelity simulation environment. Overall, the proposed co-simulation method can interface several simulation tools within a DT, thereby incorporating different communication protocols and realistic visualization capabilities. This creates unprecedented opportunities to combine different software applications and leverage the benefits of each tool

Physiological Characterization of Need for Assistance in Rescue Missions with Drones

The use of drones is recently gaining particular interest in the field of search and rescue. However, particular skills are still required to actively operate in a mission without crashing the drone. This limits their effective and efficient employment in real missions. Thus, to assist the rescuers operating in stressful conditions, there is a need to detect an increase of workload that could compromise the outcome of the mission. In this work a simulator is designed and used to induce different levels of cognitive workload related to search and rescue missions. Physiological signals are recorded and features are extracted from them to estimate cognitive workloads. The NASA Task Load Index is used as subjective self-report workload reference. Then, performance is recorded to objectively evaluate the execution of the tasks. Finally, the analysis of variance (ANOVA) is used to verify intra- and inter-subject variability. Results show statistical decrease of the mean normal-to-normal (NN) interval with an increase of cognitive workload. Moreover, it is observed a decrease of performance while an increase of cognitive workload exists. This information can be used to detect the need for assistance