Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home

Belmonte, Lidia M.; García, Arturo S.; Morales, Rafael; Rosa, Francisco López de la; Fernández-Caballero, Antonio

doi:10.3390/s21030908

Cited by 15 publications

(8 citation statements)

References 43 publications

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“…In this sense, the results showed that the trajectory planner correctly determines the references for the UAV's position and yaw angle according to the position and orientation of the person, while the 3D virtual quadrotor reproduces the flight based on the UAV state information received from the UAV Simulator. More details about the trajectory planner operation can be found in our previous works [13,24].…”

Section: Discussionmentioning

confidence: 99%

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Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

et al. 2021

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This work is part of an ongoing research project to develop an unmanned flying social robot to monitor dependants at home in order to detect the person’s state and bring the necessary assistance. In this sense, this paper focuses on the description of a virtual reality (VR) simulation platform for the monitoring process of an avatar in a virtual home by a rotatory-wing autonomous unmanned aerial vehicle (UAV). This platform is based on a distributed architecture composed of three modules communicated through the message queue telemetry transport (MQTT) protocol: the UAV Simulator implemented in MATLAB/Simulink, the VR Visualiser developed in Unity, and the new emotion recognition (ER) system developed in Python. Using a face detection algorithm and a convolutional neural network (CNN), the ER System is able to detect the person’s face in the image captured by the UAV’s on-board camera and classify the emotion among seven possible ones (surprise; fear; happiness; sadness; disgust; anger; or neutral expression). The experimental results demonstrate the correct integration of this new computer vision module within the VR platform, as well as the good performance of the designed CNN, with around 85% in the F1-score, a mean of the precision and recall of the model. The developed emotion detection system can be used in the future implementation of the assistance UAV that monitors dependent people in a real environment, since the methodology used is valid for images of real people.

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Section: Discussionmentioning

confidence: 99%

“…In the current implementation of the planner, it is possible to configure the tracking trajectory to define the height at which the UAV flies, as well as the trajectory (circular or elliptical) it describes around the person, to suit the user's preferences. Details of this planner can be found in [24].…”

Section: Uav Simulatormentioning

confidence: 99%

Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

et al. 2021

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“…The link between the headset and the robotic platform was created using the Message Queueing Telemetry Transport (MQTT) communication protocol [ 25 ]. MQTT is a lightweight protocol for IoT messaging and is widely used in robot control systems [ 26 , 27 , 28 , 29 , 30 , 31 ]. It was our choice because it has a small computational overhead and was easy to integrate into our system.…”

Section: Methodsmentioning

confidence: 99%

PlatypOUs—A Mobile Robot Platform and Demonstration Tool Supporting STEM Education

Rácz

Noboa

Détár

et al. 2022

Sensors

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Given the rising popularity of robotics, student-driven robot development projects are playing a key role in attracting more people towards engineering and science studies. This article presents the early development process of an open-source mobile robot platform—named PlatypOUs—which can be remotely controlled via an electromyography (EMG) appliance using the MindRove brain–computer interface (BCI) headset as a sensor for the purpose of signal acquisition. The gathered bio-signals are classified by a Support Vector Machine (SVM) whose results are translated into motion commands for the mobile platform. Along with the physical mobile robot platform, a virtual environment was implemented using Gazebo (an open-source 3D robotic simulator) inside the Robot Operating System (ROS) framework, which has the same capabilities as the real-world device. This can be used for development and test purposes. The main goal of the PlatypOUs project is to create a tool for STEM education and extracurricular activities, particularly laboratory practices and demonstrations. With the physical robot, the aim is to improve awareness of STEM outside and beyond the scope of regular education programmes. It implies several disciplines, including system design, control engineering, mobile robotics and machine learning with several application aspects in each. Using the PlatypOUs platform and the simulator provides students and self-learners with a firsthand exercise, and teaches them to deal with complex engineering problems in a professional, yet intriguing way.

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“…The implementation of a completely functional VE facilitates learning among people of various ages, and is safer than real-world experience [ 14 ]. VR is also cost-efficient and capable of reducing potential risks [ 15 , 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space

Khan

Muhammad

Hussain

et al. 2021

Sensors

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Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.

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Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home

Cited by 15 publications

References 43 publications

Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

PlatypOUs—A Mobile Robot Platform and Demonstration Tool Supporting STEM Education

An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space

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