System-controlled user interaction within the service robotic control architecture MASSiVE

Robotica ◽  
2007 ◽  
Vol 25 (2) ◽  
pp. 237-244 ◽  
Author(s):  
Oliver Prenzel ◽  
Christian Martens ◽  
Marco Cyriacks ◽  
Chao Wang ◽  
Axel Gräser
Keyword(s):  
A Priori ◽  
User Involvement ◽  
User Interaction ◽  
Interface Layer ◽  
Robotic System ◽  
Control Architecture ◽  
Task Execution ◽  
User Interactions ◽  
Seamless Integration ◽  
Task Knowledge

SUMMARYThis paper presents an approach to reduce the technical complexity of a service robotic system by means of systematic and well-balanced user-involvement. By taking advantage of the user's cognitive capabilities during task execution, a technically manageable robotic system, which is able to execute tasks on a high level of abstraction reliably and robustly, emerges. For the realisation of this approach, the control architecture MASSiVE has been implemented, which is used for the control of the rehabilitation robot FRIEND II. It supports task execution on the basis of a priori defined and formally verified task-knowledge. This task-knowledge contains all possible sequences of operations as well as the symbolic representation of objects required for the execution of a specific task. The seamless integration of user interactions into this task-knowledge, in combination with MASSiVE's user-adapted human–machine interface layer, enables the system to deliberately interact with the user during run-time.

scholarly journals Orchestration and Situation Awareness in an Assistance System for Assembly Tasks

2021 ◽  
pp. 332-343
Author(s):  
Wernher Behrendt ◽  
Felix Strohmeier
Keyword(s):  
Situation Awareness ◽  
A Priori ◽  
Assistance System ◽  
Tutoring Systems ◽  
Task Knowledge ◽  
Enterprise Level ◽  
Assistive Systems ◽  
Personal Assistants ◽  
User Friendly ◽  
Assembly Tasks

AbstractWe report on the design, specification and implementation of a situation awareness module used for assistive systems in manufacturing, in the context of Industry 4.0. A recent survey of research done in Germany and Europe, concerning assistive technology in industry shows a very high potential for “intelligent assistance” by combining smart sensors, networking and AI. While the state of the art concerning actual technology in industrial use points more towards user-friendly, speech-based interaction with personal assistants for information retrieval (typically of in-house documentation), the research presented here addresses an enterprise-level assistance system that is supported by a number of specialized Assistance Units that can be customized to the end users’ specifications and that range from tutoring systems to tele-robotics. Key to the approach is situation awareness, which is achieved through a combination of a-priori, task knowledge modelling and dynamic situation assessment on the basis of observation streams coming from sensors, cameras and microphones. The paper describes a working fragment of the industrial task description language and its extensions to cover also the triggering of assistive interventions when the observation modules have sent data that warrants such interventions.

scholarly journals A Graph Mining Approach for Ranking and Discovering the Interesting Frequent Subgraph Patterns

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Saif Ur Rehman ◽  
Kexing Liu ◽  
Tariq Ali ◽  
Asif Nawaz ◽  
Simon James Fong
Keyword(s):  
Graph Mining ◽  
A Priori ◽  
Research Work ◽  
User Involvement ◽  
Threshold Value ◽  
Research Field ◽  
Frequent Subgraph Mining ◽  
Graph Data ◽  
Frequent Subgraph ◽  
Pattern Growth

AbstractGraph mining is a well-established research field, and lately it has drawn in considerable research communities. It allows to process, analyze, and discover significant knowledge from graph data. In graph mining, one of the most challenging tasks is frequent subgraph mining (FSM). FSM consists of applying the data mining algorithms to extract interesting, unexpected, and useful graph patterns from the graphs. FSM has been applied to many domains, such as graphical data management and knowledge discovery, social network analysis, bioinformatics, and security. In this context, a large number of techniques have been suggested to deal with the graph data. These techniques can be classed into two primary categories: (i) a priori-based FSM approaches and (ii) pattern growth-based FSM approaches. In both of these categories, an extensive research work is available. However, FSM approaches are facing some challenges, including enormous numbers of frequent subgraph patterns (FSPs); no suitable mechanism for applying ranking at the appropriate level during the discovery process of the FSPs; extraction of repetitive and duplicate FSPs; user involvement in supplying the support threshold value; large number of subgraph candidate generation. Thus, the aim of this research is to make do with the challenges of enormous FSPs, avoid duplicate discovery of FSPs, and use the ranking for such patterns. Therefore, to address these challenges a new FSM framework A RAnked Frequent pattern-growth Framework (A-RAFF) is suggested. Consequently, A-RAFF provides an efficacious answer to these challenges through the initiation of a new ranking measure called FSP-Rank. The proposed ranking measure FSP-Rank effectively reduced the duplicate and enormous frequent patterns. The effectiveness of the techniques proposed in this study is validated by extensive experimental analysis using different benchmark and synthetic graph datasets. Our experiments have consistently demonstrated the promising empirical results, thus confirming the superiority and practical feasibility of the proposed FSM framework.

scholarly journals Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256696
Author(s):  
Anna Keuchenius ◽  
Petter Törnberg ◽  
Justus Uitermark
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Network Analysis ◽  
Language Processing ◽  
User Interaction ◽  
User Interactions ◽  
Online Interactions ◽  
Network Analyses ◽  
Social Media Platforms ◽  
Signed Network

Despite the prevalence of disagreement between users on social media platforms, studies of online debates typically only look at positive online interactions, represented as networks with positive ties. In this paper, we hypothesize that the systematic neglect of conflict that these network analyses induce leads to misleading results on polarized debates. We introduce an approach to bring in negative user-to-user interaction, by analyzing online debates using signed networks with positive and negative ties. We apply this approach to the Dutch Twitter debate on ‘Black Pete’—an annual Dutch celebration with racist characteristics. Using a dataset of 430,000 tweets, we apply natural language processing and machine learning to identify: (i) users’ stance in the debate; and (ii) whether the interaction between users is positive (supportive) or negative (antagonistic). Comparing the resulting signed network with its unsigned counterpart, the retweet network, we find that traditional unsigned approaches distort debates by conflating conflict with indifference, and that the inclusion of negative ties changes and enriches our understanding of coalitions and division within the debate. Our analysis reveals that some groups are attacking each other, while others rather seem to be located in fragmented Twitter spaces. Our approach identifies new network positions of individuals that correspond to roles in the debate, such as leaders and scapegoats. These findings show that representing the polarity of user interactions as signs of ties in networks substantively changes the conclusions drawn from polarized social media activity, which has important implications for various fields studying online debates using network analysis.

Task-oriented hierarchical control architecture for swarm robotic system

2016 ◽  
Vol 16 (4) ◽  
pp. 579-596 ◽  
Author(s):  
Yuquan Leng ◽  
Cen Yu ◽  
Wei Zhang ◽  
Yang Zhang ◽  
Xu He ◽  
...  
Keyword(s):  
Hierarchical Control ◽  
Robotic System ◽  
Control Architecture ◽  
Hierarchical Control Architecture ◽  
Task Oriented

An Investigation of User Behaviour Consistency for Context-Aware Information Retrieval Systems

2009 ◽  
Vol 1 (4) ◽  
pp. 69-90 ◽  
Author(s):  
Adam Grzywaczewski ◽  
Rahat Iqbal ◽  
Anne James ◽  
John Halloran
Keyword(s):  
Information Retrieval ◽  
User Study ◽  
User Interaction ◽  
Context Aware ◽  
Interaction Patterns ◽  
Frequent User ◽  
User Interactions ◽  
Information Retrieval Systems ◽  
Finite Set ◽  
Domain Expertise

Users interact with the Internet in dynamic environments that require the IR system to be context aware. Modern IR systems take advantage of user location, browsing history or previous interaction patterns, but a significant number of contextual factors that impact the user information retrieval process are not yet available. Parameters like the emotional state of the user and user domain expertise affect the user experience significantly but are not understood by IR systems. This article presents results of a user study that simplifies the way context in IR and its role in the systems’ efficiency is perceived. The study supports the hypothesis that the number of user interaction contexts and the problems that a particular user is trying to solve is related to lifestyle. Therefore, the IR system’s perception of the interaction context can be reduced to a finite set of frequent user interactions.

Human–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Matteo Lavit Nicora ◽  
Roberto Ambrosetti ◽  
Gloria J. Wiens ◽  
Irene Fassi
Keyword(s):  
Situation Awareness ◽  
Production Efficiency ◽  
A Priori ◽  
Open Loop ◽  
Human Robot Interaction ◽  
Smart Manufacturing ◽  
Seamless Integration ◽  
Robot Controller ◽  
Human Robot Collaboration ◽  
Different Levels

Abstract To enable safe and effective human–robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition, and prediction into the robot controller is critical for real-time awareness, response, and communication inside a heterogeneous environment (robots, humans, and equipment). The specific research objective is to provide the robot Proactive Adaptive Collaboration Intelligence (PACI) and switching logic within its control architecture in order to give the robot the ability to optimally and dynamically adapt its motions, given a priori knowledge and predefined execution plans for its assigned tasks. The challenge lies in augmenting the robot’s decision-making process to have greater situation awareness and to yield smart robot behaviors/reactions when subject to different levels of human–robot interaction, while maintaining safety and production efficiency. Robot reactive behaviors were achieved via cost function-based switching logic activating the best suited high-level controller. The PACI’s underlying segmentation and switching logic framework is demonstrated to yield a high degree of modularity and flexibility. The performance of the developed control structure subjected to different levels of human–robot interactions was validated in a simulated environment. Open-loop commands were sent to the physical e.DO robot to demonstrate how the proposed framework would behave in a real application.

Inverse Kinematic and Control Architecture of a Slave Manipulator for MR-Guided Brain Biopsy

2008 ◽  
Author(s):  
C. Raoufi ◽  
A. A. Goldenberg ◽  
W. Kucharczyk ◽  
H. Hadian
Keyword(s):  
Modular Design ◽  
Brain Biopsy ◽  
Inverse Kinematic ◽  
Robotic System ◽  
Control Architecture ◽  
Neurosurgical Procedures ◽  
Biopsy Needle ◽  
Mri Guided ◽  
Position And Orientation ◽  
And Control

In this paper, the inverse kinematic and control paradigm of a novel tele-robotic system for MRI-guided interventions for closed-bore MRI-guided brain biopsy is presented. Other candidate neurosurgical procedures enabled by this system would include thermal ablation, radiofrequency ablation, deep brain stimulators, and targeted drug delivery. The control architecture is also reported. The design paradigm is fundamentally based on a modular design configuration of the slave manipulator that is performing tasks inside MR scanner. The tele-robotic system is a master-slave system. The master manipulator consists of three units including: (i) the navigation module; (ii) the biopsy module; and (iii) the surgical arm. Navigation and biopsy modules were designed to undertake the alignment and advancement of the surgical needle respectively. The biopsy needle is held and advanced by the biopsy module. The biopsy module is attached to the navigation module. All three units are held by a surgical arm. The main challenge in the control of the biopsy needle using the proposed navigation module is to adjust a surgical tool from its initial position and orientation to a final position and orientation. In a typical brain biopsy operation, the desired task is to align the biopsy needle with a target knowing the positions of both the target in the patient’s skull and the entry point on the surface of the skull. In this paper, the mechanical design, control paradigms, and inverse kinematics model of the robot are reported.

Anxiety detecting robotic system – towards implicit human-robot collaboration

Robotica ◽  
2004 ◽  
Vol 22 (1) ◽  
pp. 85-95 ◽  
Author(s):  
Pramila Rani ◽  
Nilanjan Sarkar ◽  
Craig A. Smith ◽  
Leslie D. Kirby
Keyword(s):  
Mobile Robot ◽  
Affective State ◽  
Robotic System ◽  
Control Architecture ◽  
Affect Recognition ◽  
Implicit Communication ◽  
Physiological Indices ◽  
Robot Cooperation ◽  
Human Robot Collaboration ◽  
Qualitative Analyses

A novel affect-sensitive human-robot cooperative framework is presented in this paper. Peripheral physiological indices are measured through wearable biofeedback sensors to detect the affective state of the human. Affect recognition is performed through both quantitative and qualitative analyses. A subsumption control architecture sensitive to the affective state of the human is proposed for a mobile robot. Human-robot cooperation experiments are performed where the robot senses the affective state of the human and responds appropriately. The results presented here validate the proposed framework and demonstrate a new way of achieving implicit communication between a human and a robot.

How to co-produce climate services in collaboration with users? Insights from a story map development process.

2020 ◽  
Author(s):  
Bente Vollstedt ◽  
Jana Koerth ◽  
Athanasios Vafeidis
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
User Involvement ◽  
User Interaction ◽  
User Needs ◽  
Adaptation Measures ◽  
Climate Services ◽  
Story Map ◽  
Climate Service ◽  
In The Beginning

<p>The actual use of climate services depends on the identification of real user needs and their integration into the service. Thus, for the production of climate services user involvement is a vital component. Descriptions of practical approaches in the scientific literature are rare but necessary in order to gain better user insights and to improve the user-provider interface. In the frame of the ERA4CS project EVOKED, we apply the user-centered Living Lab approach to develop climate services with the objective to support the coastal adaptation process in Flensburg, a city vulnerable to coastal flooding due to sea-level rise. The aim is to transform climate information into valuable and useable climate services for users. In the beginning of the project we identified the climate service user needs of the community. Thereafter, we co-produced a web-based story map in collaboration with the users, as an information tool for the general public. The story map includes information on sea-level rise and its potential impacts and displays information on relevant adaptations options. For the production process of the story map we started with a compilation phase by drafting a first version of the story map from the providers’ perspective, followed by a demonstration and online feedback phase with user involvement. Based on the received feedback, we adjusted the story map to meet user needs. Results showed the need for clearer visualization of e.g. exposed locations in the city and more detailed information on adaptation measures. Preliminary findings indicate that the active provider-user interaction for the climate service may lead to long-term adaptation action.</p>

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