RoboCup@Home

2009 ◽  
Vol 10 (3) ◽  
pp. 392-426 ◽  
Author(s):  
Thomas Wisspeintner ◽  
Tijn van der Zant ◽  
Luca Iocchi ◽  
Stefan Schiffer
Keyword(s):  
Scientific Progress ◽  
Human Robot Interaction ◽  
Assistive Robotics ◽  
Domestic Service ◽  
Human Interaction ◽  
Service Robots ◽  
Wide Range ◽  
Community Effort ◽  
Large Effort ◽  
High Level

Being part of the RoboCup initiative, the RoboCup@Home league targets the development and deployment of autonomous service and assistive robot technology being essential for future personal domestic applications. The domain of domestic service and assistive robotics implicates a wide range of possible problems. The primary reasons for this include the large amount of uncertainty in the dynamic and non-standardized environments of the real world, and the related human interaction. Furthermore, the application orientation requires a large effort towards high level integration combined with a demand for general robustness of the systems. This article details the need for interdisciplinary community effort to iteratively identify related problems, to define benchmarks, to test and, finally, to solve the problems. The concepts and the implementation of the RoboCup@Home initiative as a combination of scientific exchange and competition is presented as an effi cient method to accelerate and focus technological and scientific progress in the domain of domestic service robots. Finally, the progress in terms of performance increase in the benchmarks and technological advancements is evaluated and discussed. Keywords: Domestic Service Robotics, Application, Uncertainty, Benchmark, Competition, Human–Robot Interaction, RoboCup@Home

scholarly journals Deep Learning Based BCI Control of a Robotic Service Assistant Using Intelligent Goal Formulation

2018 ◽  
Author(s):  
D. Kuhner ◽  
L.D.J. Fiederer ◽  
J. Aldinger ◽  
F. Burget ◽  
M. Völker ◽  
...  
Keyword(s):  
Deep Learning ◽  
User Study ◽  
Human Robot Interaction ◽  
Service Robots ◽  
Referring Expressions ◽  
Non Invasive ◽  
Neuronal Signal ◽  
High Level ◽  
User Friendly ◽  
Robotic Tasks

AbstractAs autonomous service robots become more affordable and thus available for the general public, there is a growing need for user-friendly interfaces to control these systems. Control interfaces typically get more complicated with increasing complexity of the robotic tasks and the environment. Traditional control modalities as touch, speech or gesture commands are not necessarily suited for all users. While non-expert users can make the effort to familiarize themselves with a robotic system, paralyzed users may not be capable of controlling such systems even though they need robotic assistance most. In this paper, we present a novel framework, that allows these users to interact with a robotic service assistant in a closed-loop fashion, using only thoughts. The system is composed of several interacting components: non-invasive neuronal signal recording and co-adaptive deep learning which form the brain-computer interface (BCI), high-level task planning based on referring expressions, navigation and manipulation planning as well as environmental perception. We extensively evaluate the BCI in various tasks, determine the performance of the goal formulation user interface and investigate its intuitiveness in a user study. Furthermore, we demonstrate the applicability and robustness of the system in real world scenarios, considering fetch-and-carry tasks and tasks involving human-robot interaction. As our results show, the system is capable of adapting to frequent changes in the environment and reliably accomplishes given tasks within a reasonable amount of time. Combined with high-level planning using referring expressions and autonomous robotic systems, interesting new perspectives open up for non-invasive BCI-based human-robot interactions.

scholarly journals Accessible Human-Robot Interaction for Telepresence Robots: A Case Study

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Katherine M. Tsui ◽  
James M. Dalphond ◽  
Daniel J. Brooks ◽  
Mikhail S. Medvedev ◽  
Eric McCann ◽  
...  
Keyword(s):  
User Interface ◽  
Autonomous Navigation ◽  
Active Role ◽  
Target Population ◽  
Human Robot Interaction ◽  
Assistive Robotics ◽  
Human Interaction ◽  
Telepresence Robot ◽  
Telepresence Robots

AbstractThe quality of life of people with special needs, such as residents of healthcare facilities, may be improved through operating social telepresence robots that provide the ability to participate in remote activities with friends or family. However, to date, such platforms do not exist for this population.Methodology: Our research utilized an iterative, bottomup, user-centered approach, drawing upon our assistive robotics experiences. Based on the findings of our formative user studies, we developed an augmented reality user interface for our social telepresence robot. Our user interface focuses primarily on the human-human interaction and communication through video, providing support for semi-autonomous navigation. We conducted a case study (n=4) with our target population in which the robot was used to visit a remote art gallery.Results: All of the participants were able to operate the robot to explore the gallery, form opinions about the exhibits, and engage in conversation.Significance: This case study demonstrates that people from our target population can successfully engage in the active role of operating a telepresence robot.

scholarly journals An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6520
Author(s):  
Raquel Fuentetaja ◽  
Angel García-Olaya ◽  
Javier García ◽  
José Carlos González ◽  
Fernando Fernández
Keyword(s):  
Autonomous Robots ◽  
Automated Planning ◽  
Human Robot Interaction ◽  
Assistive Robotics ◽  
Use Cases ◽  
General Definition ◽  
Planning Model ◽  
Level Control ◽  
Robot Interaction ◽  
High Level

Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard Planning Domain Definition Language (PDDL) format, are still very hard to formalize for non expert engineers when the use case to model is complex. Human Robot Interaction (HRI) is one of those complex environments. This manuscript describes the rationale followed to design a planning model able to control social autonomous robots interacting with humans. It is the result of the authors’ experience in modeling use cases for Social Assistive Robotics (SAR) in two areas related to healthcare: Comprehensive Geriatric Assessment (CGA) and non-contact rehabilitation therapies for patients with physical impairments. In this work a general definition of these two use cases in a unique planning domain is proposed, which favors the management and integration with the software robotic architecture, as well as the addition of new use cases. Results show that the model is able to capture all the relevant aspects of the Human-Robot interaction in those scenarios, allowing the robot to autonomously perform the tasks by using a standard planning-execution architecture.

ORAL HISTORY SOURCES AS LEARNING MATERIALS: A CASE STUDY OF THE NATIONAL UNIVERSITY OF SCIENCE AND TECHNOLOGY

2016 ◽  
Vol 3 (2) ◽  
pp. 82-93
Author(s):  
Gugulethu Shamaine Nkala ◽  
Rodreck David
Keyword(s):  
Oral History ◽  
Learning Experience ◽  
Science And Technology ◽  
Group Discussion ◽  
Human Interaction ◽  
Learning Material ◽  
Wide Range ◽  
National Archives ◽  
National University ◽  
Set Up

Knowledge presented by Oral History (OH) is unique in that it shares the tacit perspective, thoughts, opinions and understanding of the interviewee in its primary form. While teachers, lecturers and other education specialists have at their disposal a wide range of primary, secondary and tertiary sources upon which to relate and share or impart knowledge, OH presents a rich source of information that can improve the learning and knowledge impartation experience. The uniqueness of OH is presented in the following advantages of its use: it allows one to learn about the perspectives of individuals who might not otherwise appear in the historical record; it allows one to compensate for the digital age; one can learn different kinds of information; it provides historical actors with an opportunity to tell their own stories in their own words; and it offers a rich opportunity for human interaction. This article discusses the placement of oral history in the classroom set-up by investigating its use as a source of learning material presented by the National Archives of Zimbabwe to students in the Department of Records and Archives Management at the National University of Science and Technology (NUST). Interviews and a group discussion were used to gather data from an archivist at the National Archives of Zimbabwe, lecturers and students in the Department of Records and Archives Management at NUST, respectively. These groups were approached on the usability, uniqueness and other characteristics that support this type of knowledge about OH in a tertiary learning experience. The findings indicate several qualities that reflect the richness of OH as a teaching source material in a classroom set-up. It further points to weak areas that may be addressed where the source is considered a viable strategy for knowledge sharing and learning. The researchers present a possible model that can be used to champion the use of this rich knowledge source in classroom education at this university and in similar set-ups. 

The way of value of Correlation of genomic DNA microsatellite loci and live weight of Chukchi reindeer

2020 ◽  
pp. 27-32
Author(s):  
V. Dodokhov ◽  
N. Pavlova ◽  
T. Rumyantseva ◽  
L. Kalashnikova
Keyword(s):  
Microsatellite Markers ◽  
Agricultural Production ◽  
Live Weight ◽  
Biodiversity Loss ◽  
Tribal Community ◽  
High Germination ◽  
Wide Range ◽  
The Mean ◽  
High Level ◽  
Dna Microsatellite

The article presents the genetic characteristic of the Chukchi reindeer breed. The object of the study was of the Chukchi reindeer. In recent years, the number of reindeer of the Chukchi breed has declined sharply. Reduced reindeer numbers could lead to biodiversity loss. The Chukchi breed of deer has good meat qualities, has high germination viability and is adapted in adverse tundra conditions of Yakutia. Herding of the Chukchi breed of deer in Yakutia are engaged only in the Nizhnekolymsky district. There are four generic communities and the largest of which is the agricultural production cooperative of nomadic tribal community «Turvaurgin», which was chosen to assess the genetic processes of breed using microsatellite markers: Rt6, BMS1788, Rt 30, Rt1, Rt9, FCB193, Rt7, BMS745, C 143, Rt24, OheQ, C217, C32, NVHRT16, T40, C276. It was found that microsatellite markers have a wide range of alleles and generally have a high informative value for identifying of genetic differences between animals and groups of animal. The number of identified alleles is one of the indicators of the genetic diversity of the population. The total number of detected alleles was 127. The Chukchi breed of deer is characterized by a high level of heterozygosity, and the random crossing system prevails over inbreeding in the population. On average, there were 7.9 alleles (Na) per locus, and the mean number of effective alleles (Ne) was 4.1. The index of fixation averaged 0.001. The polymorphism index (PIC) ranged from 0.217 to 0.946, with an average of 0.695.

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Soil Chemical Pollution and Aggressive Pathologies

2018 ◽  
Vol 69 (8) ◽  
pp. 2278-2282
Author(s):  
Stelian Ioan Morariu ◽  
Letitia Doina Duceac ◽  
Alina Costina Luca ◽  
Florina Popescu ◽  
Liliana Pavel ◽  
...  
Keyword(s):  
Health Care Professionals ◽  
Scientific Progress ◽  
Volcanic Eruptions ◽  
Chemical Pollution ◽  
Optimal Parameters ◽  
Chemical Pollutants ◽  
Wide Range ◽  
Health Physician ◽  
Solid Liquid

Maintaining the soil in optimal parameters is vital for mankind, given its essential role in providing the alimentary base, as well as its extremely slow formation and regeneration (hundreds or thousands of years). The direct and indirect pollution of the soil and especially its chemical pollution represent a corollary of other types of pollution, given that it is produced by solid, liquid and gaseous residues. It may be involved in a wide range of diseases (respiratory, cardiovascular, digestive, renal, haematological, osteoarticular, neurological) of allergic, infectious, degenerative or neoplastic nature, from infancy to the old age. Although there are natural causes of soil pollution (e.g. volcanic eruptions), most pollutants come from human activities, which are the most incriminated in its pollution, degradation and erosion at an accelerated pace. The growing concern of all nations for the adoption of measures to limit the chemical pollution of the soil is partially found so far in viable and effective solutions intended to combat soil contamination and degradation and ensure its restoration. Chemical industrialization leads to technical and scientific progress, but at the same time it can develop related pathologies, which means that the role of the occupational health physician is essential in ensuring prophylaxis and the early detection of occupational diseases. Besides that, the role of the pediatrician is equally precious for the detection of specific diseases caused by chemical pollutants to children, because they will develop into adults with pathological stigma.The chemical pollution of the soil is a major challenge for ecologists, given that it is an important risk factor for many types of afflictions. It requires maximum attention from civil society, health care professionals and government institutions. The specialist in occupational medicine, as well as the pediatrician bear an essential responsibility in both, prevention and treatment.

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