Electronics

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22 pages, 29722 KiB

Open AccessArticle

Prospects of Robots in Assisted Living Environment

by Safdar Mahmood, Kwame Owusu Ampadu, Konstantinos Antonopoulos, Christos Panagiotou, Sergio Andres Pertuz Mendez, Ariel Podlubne, Christos Antonopoulos, Georgios Keramidas, Michael Hübner, Diana Goehringer and Nikolaos Voros

Electronics 2021, 10(17), 2062; https://doi.org/10.3390/electronics10172062 - 26 Aug 2021

Cited by 5 | Viewed by 2695

Abstract

From caretaking activities for elderly people to being assistive in healthcare setup, mobile and non-mobile robots have the potential to be highly applicable and serviceable. The ongoing pandemic has shown that human-to-human contact in healthcare institutions and senior homes must be limited. In [...] Read more.

From caretaking activities for elderly people to being assistive in healthcare setup, mobile and non-mobile robots have the potential to be highly applicable and serviceable. The ongoing pandemic has shown that human-to-human contact in healthcare institutions and senior homes must be limited. In this scenario, elderlies and immunocompromised individuals must be exclusively protected. Robots are a promising way to overcome this problem in assisted living environments. In addition, the advent of AI and machine learning will pave a way for intelligent robots with cognitive abilities, while enabling them to be more aware of their surroundings. In this paper, we discuss the general perspectives, potential research opportunities, and challenges arising in the area of robots in assisted living environments and present our research work pertaining to certain application scenarios, i.e., robots in rehabilitation and robots in hospital environments and pandemics, which, in turn, exhibits the growing prospects and interdisciplinary nature of the field of robots in assisted living environment. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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13 pages, 2201 KiB

Open AccessArticle

Advancing Stress Detection Methodology with Deep Learning Techniques Targeting UX Evaluation in AAL Scenarios: Applying Embeddings for Categorical Variables

by Alexandros Liapis, Evanthia Faliagka, Christos P. Antonopoulos, Georgios Keramidas and Nikolaos Voros

Electronics 2021, 10(13), 1550; https://doi.org/10.3390/electronics10131550 - 26 Jun 2021

Cited by 6 | Viewed by 3305

Abstract

Physiological measurements have been widely used by researchers and practitioners in order to address the stress detection challenge. So far, various datasets for stress detection have been recorded and are available to the research community for testing and benchmarking. The majority of the [...] Read more.

Physiological measurements have been widely used by researchers and practitioners in order to address the stress detection challenge. So far, various datasets for stress detection have been recorded and are available to the research community for testing and benchmarking. The majority of the stress-related available datasets have been recorded while users were exposed to intense stressors, such as songs, movie clips, major hardware/software failures, image datasets, and gaming scenarios. However, it remains an open research question if such datasets can be used for creating models that will effectively detect stress in different contexts. This paper investigates the performance of the publicly available physiological dataset named WESAD (wearable stress and affect detection) in the context of user experience (UX) evaluation. More specifically, electrodermal activity (EDA) and skin temperature (ST) signals from WESAD were used in order to train three traditional machine learning classifiers and a simple feed forward deep learning artificial neural network combining continues variables and entity embeddings. Regarding the binary classification problem (stress vs. no stress), high accuracy (up to 97.4%), for both training approaches (deep-learning, machine learning), was achieved. Regarding the stress detection effectiveness of the created models in another context, such as user experience (UX) evaluation, the results were quite impressive. More specifically, the deep-learning model achieved a rather high agreement when a user-annotated dataset was used for validation. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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25 pages, 2753 KiB

Open AccessArticle

Kinematic of the Position and Orientation Synchronization of the Posture of a n DoF Upper-Limb Exoskeleton with a Virtual Object in an Immersive Virtual Reality Environment

by Deyby Huamanchahua, Adriana Vargas-Martinez and Ricardo Ramirez-Mendoza

Electronics 2021, 10(9), 1069; https://doi.org/10.3390/electronics10091069 - 30 Apr 2021

Cited by 9 | Viewed by 3024

Abstract

Exoskeletons are an external structural mechanism with joints and links that work in tandem with the user, which increases, reinforces, or restores human performance. Virtual Reality can be used to produce environments, in which the intensity of practice and feedback on performance can [...] Read more.

Exoskeletons are an external structural mechanism with joints and links that work in tandem with the user, which increases, reinforces, or restores human performance. Virtual Reality can be used to produce environments, in which the intensity of practice and feedback on performance can be manipulated to provide tailored motor training. Will it be possible to combine both technologies and have them synchronized to reach better performance? This paper consists of the kinematics analysis for the position and orientation synchronization between an n DoF upper-limb exoskeleton pose and a projected object in an immersive virtual reality environment using a VR headset. To achieve this goal, the exoskeletal mechanism is analyzed using Euler angles and the Pieper technique to obtain the equations that lead to its orientation, forward, and inverse kinematic models. This paper extends the author’s previous work by using an early stage upper-limb exoskeleton prototype for the synchronization process. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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16 pages, 1094 KiB

Open AccessArticle

Secure Autonomous Cloud Brained Humanoid Robot Assisting Rescuers in Hazardous Environments

by Georgios Angelopoulos, Nikolaos Baras and Minas Dasygenis

Electronics 2021, 10(2), 124; https://doi.org/10.3390/electronics10020124 - 8 Jan 2021

Cited by 7 | Viewed by 2600

Abstract

On 31 January 2020, the World Health Organization (WHO) declared a global emergency after the discovery of a new pandemic disease that caused severe lung problems. The spread of the disease at an international level drew the attention of many researchers who attempted [...] Read more.

On 31 January 2020, the World Health Organization (WHO) declared a global emergency after the discovery of a new pandemic disease that caused severe lung problems. The spread of the disease at an international level drew the attention of many researchers who attempted to find solutions to ameliorate the problem. The implementation of robotics has been one of the proposed solutions, as automated humanoid robots can be used in many situations and limit the exposure of humans to the disease. Many humanoid robot implementations are found in the literature; however, most of them have some distinct drawbacks, such as a high cost and complexity. Our research proposes a novel, secure and efficient programmable system using a humanoid robot that is able to autonomously move and detect survivors in emergency scenarios, with the potential to communicate verbally with victims. The proposed humanoid robot is powered by the cloud and benefits from the powerful storage, computation, and communication resources of a typical modern data center. In order to evaluate the proposed system, we conducted multiple experiments in synthetic hazardous environments. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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25 pages, 5414 KiB

Open AccessFeature PaperArticle

A Multimodal User Interface for an Assistive Robotic Shopping Cart

by Dmitry Ryumin, Ildar Kagirov, Alexandr Axyonov, Nikita Pavlyuk, Anton Saveliev, Irina Kipyatkova, Milos Zelezny, Iosif Mporas and Alexey Karpov

Electronics 2020, 9(12), 2093; https://doi.org/10.3390/electronics9122093 - 8 Dec 2020

Cited by 25 | Viewed by 4446

Abstract

This paper presents the research and development of the prototype of the assistive mobile information robot (AMIR). The main features of the presented prototype are voice and gesture-based interfaces with Russian speech and sign language recognition and synthesis techniques and a high degree [...] Read more.

This paper presents the research and development of the prototype of the assistive mobile information robot (AMIR). The main features of the presented prototype are voice and gesture-based interfaces with Russian speech and sign language recognition and synthesis techniques and a high degree of robot autonomy. AMIR prototype’s aim is to be used as a robotic cart for shopping in grocery stores and/or supermarkets. Among the main topics covered in this paper are the presentation of the interface (three modalities), the single-handed gesture recognition system (based on a collected database of Russian sign language elements), as well as the technical description of the robotic platform (architecture, navigation algorithm). The use of multimodal interfaces, namely the speech and gesture modalities, make human-robot interaction natural and intuitive, as well as sign language recognition allows hearing-impaired people to use this robotic cart. AMIR prototype has promising perspectives for real usage in supermarkets, both due to its assistive capabilities and its multimodal user interface. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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19 pages, 2824 KiB

Open AccessArticle

I2E: A Cognitive Architecture Based on Emotions for Assistive Robotics Applications

by Priscila Silva Martins, Gedson Faria and Jés de Jesus Fiais Cerqueira

Electronics 2020, 9(10), 1590; https://doi.org/10.3390/electronics9101590 - 28 Sep 2020

Cited by 5 | Viewed by 1955

Abstract

Emotions and personality play an essential role in human behavior, their considerations, and decision-making. Humans infer emotions from several modals, merging them all. They are an interface between a subject’s internal and external means. This paper presents the design, implementation, and tests of [...] Read more.

Emotions and personality play an essential role in human behavior, their considerations, and decision-making. Humans infer emotions from several modals, merging them all. They are an interface between a subject’s internal and external means. This paper presents the design, implementation, and tests of the Inference of an Emotional State (I2E): a cognitive architecture based on emotions for assistive robotics applications, which uses, as inputs, emotions recognized previously by four affective modals who inferred the emotional state to an assistive robot. Unlike solutions that classify emotions, with a single sign, the architecture proposed in this article will merge four sources of information about emotions into one. For this inference to be closer to a human being, a Fuzzy System Mamdani was used to infer the user’s personalities, and a MultiLayer Perceptron (MLP) was used to infer the robot’s personality. The hypothesis tested in this work was based on the Mehrabian studies and in addition to three experts in psychologists. The I2E architecture proved to be quite efficient for identifying an emotion with various types of input. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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16 pages, 6153 KiB

Open AccessArticle

An Autonomous Human Following Caddie Robot with High-Level Driving Functions

by Jung Hyun Choi, Kangwagye Samuel, Kanghyun Nam and Sehoon Oh

Electronics 2020, 9(9), 1516; https://doi.org/10.3390/electronics9091516 - 15 Sep 2020

Cited by 4 | Viewed by 3811

Abstract

Nowadays, mobile robot platforms are utilized in various fields not only for transportation but also for other diverse services such as industrial, medical and, sports, etc. Mobile robots are also an emerging application as sports field robots, where they can help serve players [...] Read more.

Nowadays, mobile robot platforms are utilized in various fields not only for transportation but also for other diverse services such as industrial, medical and, sports, etc. Mobile robots are also an emerging application as sports field robots, where they can help serve players or even play the games. In this paper, a novel caddie robot which can autonomously follow the golfer as well as provide useful information such as golf course navigation system and weather updates, is introduced. The locomotion of the caddie robot is designed with two modes: autonomous human following mode and manual driving mode. The transition between each mode can be achieved manually or by an algorithm based on the velocity, heading angle, and inclination of the ground surface. Moreover, the transition to manual mode is activated after a caddie robot has recognized the human intention input by hand. In addition, the advanced control algorithm along with a trajectory generator for the caddie robot are developed taking into consideration the locomotion modes. Experimental results show that the proposed strategies to drive various operating modes are efficient and the robot is verified to be utilized in the golf course. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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19 pages, 4675 KiB

Open AccessArticle

Concept Design and Load Capacity Analysis of a Novel Serial-Parallel Robot for the Automatic Charging of Electric Vehicles

by Han Yuan, Qiong Wu and Lili Zhou

Electronics 2020, 9(6), 956; https://doi.org/10.3390/electronics9060956 - 8 Jun 2020

Cited by 9 | Viewed by 3840

Abstract

The automatic charging of electric vehicles is an important but challenging problem. Recently, various charging robots are proposed for electric vehicles. Most previous researches do not pay enough attention to the robots’ load capacities. Actually, providing the charging connector with adequate pushing and/or [...] Read more.

The automatic charging of electric vehicles is an important but challenging problem. Recently, various charging robots are proposed for electric vehicles. Most previous researches do not pay enough attention to the robots’ load capacities. Actually, providing the charging connector with adequate pushing and/or pulling forces is vital to guarantee a reliable electrical connection, which is a key issue for charging robot design. In this paper, we present a novel serial-parallel robot for the automatic charging of electric vehicles. This robot is based on the 3 universal-prismatic-universal (3UPU) parallel mechanism and featured by high-load capacity. We firstly address the kinematic and static models of the proposed robot, then analyze its load capacity. It is shown that the robot’s maximum load capacity depends not only on the driving ability of the prismatic joints, but also on the robot’s structural parameters and the robot’s configuration. Finally, optimizations are made and results show that the robot’s load capacity along the desired trajectory has more than doubled. Results of this paper could be useful for the development of automatic electric-vehicle-charging devices. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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19 pages, 1817 KiB

Open AccessArticle

Laplacian Support Vector Machine for Vibration-Based Robotic Terrain Classification

by Wenlei Shi, Zerui Li, Wenjun Lv, Yuping Wu, Ji Chang and Xiaochuan Li

Electronics 2020, 9(3), 513; https://doi.org/10.3390/electronics9030513 - 20 Mar 2020

Cited by 16 | Viewed by 2744

Abstract

The achievement of robot autonomy has environmental perception as a prerequisite. The hazards rendered from uneven, soft and slippery terrains, which are generally named non-geometric hazards, are another potential threat reducing the traversing efficient, and therefore receiving more and more attention from the [...] Read more.

The achievement of robot autonomy has environmental perception as a prerequisite. The hazards rendered from uneven, soft and slippery terrains, which are generally named non-geometric hazards, are another potential threat reducing the traversing efficient, and therefore receiving more and more attention from the robotics community. In the paper, the vibration-based terrain classification (VTC) is investigated by taking a very practical issue, i.e., lack of labels, into consideration. According to the intrinsic temporal correlation existing in the sampled terrain sequence, a modified Laplacian SVM is proposed to utilise the unlabelled data to improve the classification performance. To the best of our knowledge, this is the first paper studying semi-supervised learning problem in robotic terrain classification. The experiment demonstrates that: (1) supervised learning (SVM) achieves a relatively low classification accuracy if given insufficient labels; (2) feature-space homogeneity based semi-supervised learning (traditional Laplacian SVM) cannot improve supervised learning’s accuracy, and even makes it worse; (3) feature- and temporal-space based semi-supervised learning (modified Laplacian SVM), which is proposed in the paper, could increase the classification accuracy very significantly. Full article

(This article belongs to the Special Issue Robots in Assisted Living)

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