scholarly journals Westdrive X LoopAR: An Open-Access Virtual Reality Project in Unity for Evaluating User Interaction Methods during Takeover Requests

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1879 ◽  
Author(s):  
Farbod N. Nezami ◽  
Maximilian A. Wächter ◽  
Nora Maleki ◽  
Philipp Spaniol ◽  
Lea M. Kühne ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Open Access ◽  
Force Feedback ◽  
User Interaction ◽  
Human Machine Interaction ◽  
Access Cost ◽  
Cost Efficient ◽  
Further Development ◽  
Machine Interaction ◽  
Traffic Behavior

With the further development of highly automated vehicles, drivers will engage in non-related tasks while being driven. Still, drivers have to take over control when requested by the car. Here, the question arises, how potentially distracted drivers get back into the control-loop quickly and safely when the car requests a takeover. To investigate effective human–machine interactions, a mobile, versatile, and cost-efficient setup is needed. Here, we describe a virtual reality toolkit for the Unity 3D game engine containing all the necessary code and assets to enable fast adaptations to various human–machine interaction experiments, including closely monitoring the subject. The presented project contains all the needed functionalities for realistic traffic behavior, cars, pedestrians, and a large, open-source, scriptable, and modular VR environment. It covers roughly 25 km2, a package of 125 animated pedestrians, and numerous vehicles, including motorbikes, trucks, and cars. It also contains all the needed nature assets to make it both highly dynamic and realistic. The presented repository contains a C++ library made for LoopAR that enables force feedback for gaming steering wheels as a fully supported component. It also includes all necessary scripts for eye-tracking in the used devices. All the main functions are integrated into the graphical user interface of the Unity® editor or are available as prefab variants to ease the use of the embedded functionalities. This project’s primary purpose is to serve as an open-access, cost-efficient toolkit that enables interested researchers to conduct realistic virtual reality research studies without costly and immobile simulators. To ensure the accessibility and usability of the mentioned toolkit, we performed a user experience report, also included in this paper.

Design and Kinematics of a Comanipulated Robot Dedicated to Prostate Brachytherapy

Robotica ◽  
2020 ◽  
pp. 1-15
Author(s):  
Mozert Djohossou ◽  
Aziza Ben Halima ◽  
Antoine Valérie ◽  
Julien Bert ◽  
Dimitris Visvikis
Keyword(s):  
Side Effects ◽  
Operating Room ◽  
Force Feedback ◽  
Robot Kinematics ◽  
Medical Applications ◽  
Prostate Brachytherapy ◽  
Human Machine Interaction ◽  
Delta Robot ◽  
Machine Interaction ◽  
New Procedures

SUMMARY In brachytherapy, the manual implantation of seeds is not accurate leading to side effects and limiting the use of new procedures. Robotics solutions have to be fully suitable for medical applications especially considering the operating room. This paper investigates a delta robot solution for improving the accuracy of the prostate brachytherapy procedure by proposing a compact and lightweight robot. In addition, the design was thought as a comanipulated robot for a better acceptability and human–machine interaction. The robot kinematics and singularities were determined and the theoretical capability in term of resolution and force feedback was evaluated. A prototype was built in order to experimentally measure the capability of this first prototype.

scholarly journals Effectiveness of a Head Movement Interface for Steering a Vehicle in a Virtual Reality Driving Simulation

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1645
Author(s):  
Yoshiaki Saito ◽  
Kazumasa Kawashima ◽  
Masahito Hirakawa
Keyword(s):  
Virtual Reality ◽  
Head Movement ◽  
Driving Simulation ◽  
Horizontal Direction ◽  
Steering Wheel ◽  
Human Machine Interaction ◽  
Machine Interaction

Recently, virtual reality (VR) has become popular for a variety of applications, such as manufacturing and entertainment. In this study, considering that a driver’s head moves according to the motion of turning the steering wheel, we explored the effectiveness of head movement as a means for steering a vehicle in a virtual reality driving simulation. First, we analyzed the motion axes that are effective for control and found that the x (horizontal) direction, yaw rotation, and roll rotation are potential candidates. Through the implementation of a simulator, which allows participants to steer the vehicle by means of head movement, it was found that the x-axis movement was the most reliable as it reduced VR sickness while guaranteeing better usability and realistic motion. Human–machine interaction can become conceived of as symmetrical in the sense that if a machine is truly easy for humans to handle, it means that they can get the best out of it.

scholarly journals Manual Skill Generalization Enhanced by Negative Viscosity

2010 ◽  
Vol 104 (4) ◽  
pp. 2008-2019 ◽  
Author(s):  
Felix C. Huang ◽  
James L. Patton ◽  
Ferdinando A. Mussa-Ivaldi
Keyword(s):  
Force Feedback ◽  
Human Machine Interaction ◽  
Combined Training ◽  
Manual Skill ◽  
Improved Performance ◽  
Negative Viscosity ◽  
Exploratory Movements ◽  
Enhanced Learning ◽  
Machine Interaction ◽  
Shed Light

Recent human-machine interaction studies have suggested that movement augmented with negative viscosity can enhance performance and can even promote better motor learning. To test this, we investigated how negative viscosity influences motor adaptation to an environment where forces acted only in one axis of motion. Using a force-feedback device, subjects performed free exploratory movements with a purely inertia generating forces proportional to hand acceleration, negative viscosity generating destabilizing forces proportional to hand velocity, or a combination of the acceleration and velocity fields. After training, we evaluated each subject's ability to perform circular movements in only the inertial field. Combined training resulted in lowest error and revealed similar responses as inertia training in catch trials. These findings are remarkable because negative viscosity, available only during training, evidently enhanced learning when combined with inertia. This success in generalization is consistent with the ability of the nervous system to decompose the perturbing forces into velocity and acceleration dependent components. Compared with inertia, the combined group exhibited a broader range of speeds along the direction of maximal perturbing force. Broader exploration was also correlated with better performance in subsequent evaluation trials; this suggests that negative viscosity improved performance by enhancing identification of each force field. These findings shed light on a new way to enhance sensorimotor adaptation through robot-applied augmentation of mechanics.

scholarly journals Realidad Aumentada: Un sendero por descubrir [Augmented reality: A path to discovery]

2010 ◽  
Author(s):  
Leidy Diana Díaz Nieto ◽  
Sonia Patricia Nieto Aguirre
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Real World ◽  
Three Dimensional ◽  
Emerging Technology ◽  
Human Machine Interaction ◽  
Augmented Reality System ◽  
Augmented Reality Technology ◽  
Machine Interaction

Resumen El propósito de este documento es describir un campo de la realidad virtual, la realidad aumentada, término que hace referencia a una tecnología que está adquiriendo gran importancia en diferentes áreas por sus diversas aplicaciones y novedad. El objetivo de un sistema con realidad aumentada es combinar la imagen registrada por un usuario del mundo real a través de un dispositivo, con elementos tridimensionales procesados a través de una computadora. Esta característica permite a la tecnología de la realidad aumentada convertirse en un instrumento útil en áreas como educación, publicidad, desarrollo y comercialización en la industria, así como en entretenimiento, medicina y otras ciencias; se fundamenta en la combinación de otras tecnologías y es partícipe en la generación de técnicas de interacción hombre-máquina. Palabras ClaveEducación, multimedia, realidad aumentada, tecnología emergente.   Abstract The purpose of this paper is to describe a field of virtual reality, augmented reality, a term that refers to a technology that is gaining importance in different areas for various applications and novelty. The goal of an augmented reality system is to combine the image recorded by a real-world user through a device with three-dimensional elements processed through a computer. This feature allows the augmented reality technology into a useful tool in areas such as education, publicity, development and marketing in the industry as well as entertainment, medicine and other sciences, is based on a combination of other technologies and is participating techniques to generate human-machine interaction. KeywordsEducation, multimedia, augmented reality, emerging technology

scholarly journals From Interaction to Cooperation: a new approach for human-machine interaction research for closing the out-of-the-loop unfamiliarity

2020 ◽  
Author(s):  
Maximilian Alexander Wächter ◽  
Farbod Nosrat Nezami. ◽  
Nora Maleki ◽  
Philipp Spaniol ◽  
Lea Maria Kühne ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Future Research ◽  
Close Monitoring ◽  
Visual Aids ◽  
Human Machine Interaction ◽  
Out Of The Loop ◽  
Human Driver ◽  
Access Cost ◽  
Cost Efficient ◽  
Cooperation Partners

With the introduction of autonomous vehicles, drivers will be able to engage in non-related tasks while being driven. But in critical situations the car needs the support of the human driver. How do distracted drivers get back into the control-loop quickly when the car requests a take-over? To investigate effective take-over actions, we developed an interactive virtual reality experiment, that uses premises of the embodied cognition theory. Accordingly, the car should not only provide sensory input, but also help enhance the driver’s motor response by interpreting intention and thus helping to accomplish desired actions. This binds humans and machines together in becoming true cooperation partners in joint action. Therefore, we aim for a close monitoring of participants combined with sensorimotor feedforward and feedback. The presented prototype also serves as an open-access, cost-efficient toolkit that enables interested researchers to tailor the presented LoopAR tool to their own needs as part of a previously published toolkit called WestDrive. With the presented work, we hope to shift the paradigm of future research from only visual aids to full sensorimotor integration assistance.

How Artificial Intelligence, Machine Learning and Deep Learning are Radically Different?

2018 ◽  
Vol 8 (2) ◽  
pp. 1
Author(s):  
Tanya Tiwari ◽  
Tanuj Tiwari ◽  
Sanjay Tiwari
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Analysis Software ◽  
Science Data ◽  
Human Machine Interaction ◽  
Learning Techniques ◽  
Nested Hierarchy ◽  
Further Development ◽  
Machine Interaction

There is a lot of confusion these days about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). A computer system able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Artificial Intelligence has made it possible. Deep learning is a subset of machine learning, and machine learning is a subset of AI, which is an umbrella term for any computer program that does something smart. In other words, all machine learning is AI, but not all AI is machine learning, and so forth. Machine Learning represents a key evolution in the fields of computer science, data analysis, software engineering, and artificial intelligence. Machine learning (ML)is a vibrant field of research, with a range of exciting areas for further development across different methods and applications. These areas include algorithmic interpretability, robustness, privacy, fairness, inference of causality, human-machine interaction, and security. The goal of ML is never to make “perfect” guesses, because ML deals in domains where there is no such thing. The goal is to make guesses that are good enough to be useful. Deep learning is a particular kind of machine learning that achieves great power and flexibility by learning to represent the world as nested hierarchy of concepts, with each concept defined in relation to simpler concepts, and more abstract representations computed in terms of less abstract ones. This paper gives an overview of artificial intelligence, machine learning & deep learning techniques and compare these techniques.

scholarly journals Design of an Interactive Nostalgic Amusement Device with User-Friendly Tangible Interfaces for Improving the Health of Older Adults

Healthcare ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 179
Author(s):  
Chao-Ming Wang ◽  
Shih-Mo Tseng ◽  
Chen-Siang Huang
Keyword(s):  
Older Adults ◽  
Cognitive Abilities ◽  
User Interaction ◽  
Sensory Stimulation ◽  
Tangible Interfaces ◽  
Aging Effects ◽  
Human Machine Interaction ◽  
Technology Products ◽  
User Friendly ◽  
Machine Interaction

To help older adults achieve active aging, an interactive device with tangible interfaces is proposed, which combines human–machine interaction techniques and older adults’ life experiences to provide three functions: nostalgia, leisure, and entertainment. Firstly, by a review of related theories and studies, principles for designing a desirable interactive device were established. Accordingly, a prototype device with an interactive game was constructed, which was then tested in a field experiment and improved according to the users’ opinions collected by interviews. Subsequently, in a second experiment the users’ and some experts’ feedback about the system’s usability and user interaction satisfaction was collected and analyzed, and found to be reliable and valid for further evaluations of the effectiveness of the proposed system, resulting in the following findings about the older adults who have played the game: the participants become more willing to use technological devices; involving them in the game creates positive aging effects; participants become more receptive to technology products; the participating older adults’ cognitive abilities are trained and their body exercises increased, creating sensory stimulation and health promotion effects; and considering users with cognitive impairments who have stress and difficulty operating the device, the system needs to be improved in the future.

Using Virtual Prototyping Technologies to Evaluate Human-Machine-Interaction Concepts

2018 ◽  
Vol 3 ◽  
Author(s):  
Jennifer Brade ◽  
Manuel Dudczig ◽  
Philipp Klimant
Keyword(s):  
Virtual Reality ◽  
Best Practice ◽  
Virtual Prototyping ◽  
Automated Guided Vehicles ◽  
Smart Sensors ◽  
Human Machine Interaction ◽  
Innovative Products ◽  
Virtual Prototypes ◽  
Machine Interaction ◽  
Do So

Innovative products are interacting with the users based on smart sensors and algorithms. Logistics as one example is changing when automated guided vehicles are integrated in the process, supporting or even replacing workers. The way these products are interacting with humans and how they react to certain situations, will determine usability and user experience and therefore the success of use. Developing such products is based on innovative concepts that need to be evaluated and refined at early project stages. Using virtual-reality based user scenarios is one adequate option to do so. This paper describes technical as well as study-based approaches on how potential concepts are realized as virtual prototypes and evaluated by real users. It concludes with the evaluation results of a pilot study but also with general limitations and benefits as best practice advice for this kind of virtual prototyping techniques.

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