scholarly journals Cognitive Interaction Analysis in Human–Robot Collaboration Using an Assembly Task

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1317
Author(s):  
Alejandro Chacón ◽  
Pere Ponsa ◽  
Cecilio Angulo
Keyword(s):  
Interaction Analysis ◽  
Mental Workload ◽  
Cognitive Task ◽  
Physical Work ◽  
Work Skills ◽  
Dexterous Manipulation ◽  
Assembly Task ◽  
Cognitive Interaction ◽  
Human Operators ◽  
Assembly Tasks

In human–robot collaborative assembly tasks, it is necessary to properly balance skills to maximize productivity. Human operators can contribute with their abilities in dexterous manipulation, reasoning and problem solving, but a bounded workload (cognitive, physical, and timing) should be assigned for the task. Collaborative robots can provide accurate, quick and precise physical work skills, but they have constrained cognitive interaction capacity and low dexterous ability. In this work, an experimental setup is introduced in the form of a laboratory case study in which the task performance of the human–robot team and the mental workload of the humans are analyzed for an assembly task. We demonstrate that an operator working on a main high-demanding cognitive task can also comply with a secondary task (assembly) mainly developed for a robot asking for some cognitive and dexterous human capacities producing a very low impact on the primary task. In this form, skills are well balanced, and the operator is satisfied with the working conditions.

Short Vigilance Tasks are Hard Work Even If Time Flies

2016 ◽  
Vol 60 (1) ◽  
pp. 1367-1368 ◽  
Author(s):  
Victor S. Finomore ◽  
Christopher K. McClernon ◽  
Jason R. Amick ◽  
Derrick Pee ◽  
Gregory J. Funke ◽  
...  
Keyword(s):  
Task Performance ◽  
Mental Workload ◽  
Cognitive Task ◽  
Critical Role ◽  
Vigilance Task ◽  
Temporal Context ◽  
Potential Problems ◽  
Human Operators ◽  
Machine Systems ◽  
Manipulation Procedure

Vigilance research has found that observers find the task to be unpleasant and mentally demanding (Warm, Finomore, Vidulich, & Funke, 2015). However sustained attention plays a critical role in numerous operational settings where human operators must monitor automated human-machine systems in the event of potential problems. The current study extended the work from Dillard and his colleagues (Dillard, Warm, Funke, Vidulich, Nelson, Eggemeier, et al., 2013) who explored if there are other dimensions that might affect the workload associated with performing a vigilance task. The area that they explored was the temporal context of the vigilance task on its effects on task performance and perceived mental workload. Borrowing from a temporal manipulation procedure developed by Sackett and colleagues (Sackett, Meyvis, Nelson, Converse & Sackett, 2010) in which they manipulated perceived time progression (PTP) of the participant while they performed a cognitive task. Sackett et al., (2010) manipulated the PTP by developing their studies to deceive the participant into thinking the task they were performing was longer or shorter than the actual time. Upon completion of the task, participants filled out questionnaires related to the hedonic and temporal evaluation of the task. Participants that were told the task was longer than they actually participated for (time flies conditions) rated times as flying and the task more as more enjoyable.

Design and Modeling of an Electro-Rheological Fluid Based Haptic Interface

2000 ◽  
Author(s):  
C. Mavroidis ◽  
C. Pfeiffer ◽  
J. Celestino ◽  
Y. Bar-Cohen
Keyword(s):  
Analytical Modeling ◽  
Force Feedback ◽  
Haptic Interface ◽  
Dexterous Manipulation ◽  
End Effector ◽  
Jet Propulsion ◽  
Field Robots ◽  
Rutgers University ◽  
Modeling And Experiments ◽  
Human Operators

Abstract In this project, Rutgers University has teamed with the Jet Propulsion Laboratory (JPL) to pursue the development and demonstration of a novel haptic interfacing capability called MEMICA (remote MEchanical MIrroring using Controlled stiffness and Actuators). MEMICA is intended to provide human operators intuitive and interactive feeling of the stiffness and forces at remote or virtual sites in support of space, medical, underwater, virtual reality, military and field robots performing dexterous manipulation operations. The key aspect of the MEMICA system is a miniature Electrically Controlled Stiffness (ECS) element that mirrors the stiffness at remote/virtual sites. The ECS elements make use of Electro-Rheological Fluid (ERF), which is an Electro-Active Polymer (EAP), to achieve this feeling of stiffness. Forces applied at the robot end-effector due to a compliant environment will be reflected to the user by this ERF device where a change in the system viscosity will occur proportionally to the force to be transmitted. This paper describes the analytical modeling and experiments that are currently underway to develop an ERF based force feedback element.

scholarly journals Human–Robot Interaction for Improving Fuselage Assembly Tasks: A Case Study

2020 ◽  
Vol 10 (17) ◽  
pp. 5757
Author(s):  
Elena Laudante ◽  
Alessandro Greco ◽  
Mario Caterino ◽  
Marcello Fera
Keyword(s):  
Risk Index ◽  
Human Action ◽  
Human Robot Interaction ◽  
Production Performance ◽  
Robot Interaction ◽  
Speed Increase ◽  
Human Operators ◽  
Assembly Performance ◽  
Assembly Tasks

In current industrial systems, automation is a very important aspect for assessing manufacturing production performance related to working times, accuracy of operations and quality. In particular, the introduction of a robotic system in the working area should guarantee some improvements, such as risks reduction for human operators, better quality results and a speed increase for production processes. In this context, human action remains still necessary to carry out part of the subtasks, as in the case of composites assembly processes. This study aims at presenting a case study regarding the reorganization of the working activity carried out in workstation in which a composite fuselage panel is assembled in order to demonstrate, by means of simulation tool, that some of the advantages previously listed can be achieved also in aerospace industry. In particular, an entire working process for composite fuselage panel assembling will be simulated and analyzed in order to demonstrate and verify the applicability and effectiveness of human–robot interaction (HRI), focusing on working times and ergonomics and respecting the constraints imposed by standards ISO 10218 and ISO TS 15066. Results show the effectiveness of HRI both in terms of assembly performance, by reducing working times and ergonomics—for which the simulation provides a very low risk index.

Multimodal Measures of Mental Workload during Dual-Task Performance: Energetic Demands of Cognitive Processes

1992 ◽  
Vol 36 (18) ◽  
pp. 1413-1417 ◽  
Author(s):  
Richard W. Backs ◽  
Arthur M. Ryan
Keyword(s):  
Dual Task ◽  
Visual Memory ◽  
Task Difficulty ◽  
Mental Workload ◽  
Cognitive Task ◽  
Processing Load ◽  
Processing Resource ◽  
Central Processing ◽  
Cognitive Components ◽  
Energetic Model

Fifteen male volunteers participated in a dual-task study in which the central processing load of visual memory and tracking tasks and the physical load of the tracking task were orthogonally manipulated to produce varying levels of task difficulty. Multiple modes of assessment were used to measure mental workload (MWL) across difficulty levels, including: performance, subjective, cardiovascular, and metabolic. To our knowledge, this study is the first to demonstrate metabolic change with manipulations of cognitive task difficulty; others have found only baseline-to-task changes. The relation of the metabolic demands of the task to central processing resource utilization provided support for a structural energetic model of attention that may help to explain measure dissociations. The results of the present study indicated that heart period was only sensitive to central manipulations of task difficulty that affected energetic resources. Performance and subjective MWL were sensitive to all cognitive components of the tasks. We suggest that cardiovascular measures will associate with other measures only when the manipulations of task difficulty require energetic adjustment, and would expect these measures to dissociate when energetic adjustment is not required.

Human Perception of the Maximum Safe Speed of Robot Motions

1987 ◽  
Vol 31 (2) ◽  
pp. 186-190 ◽  
Author(s):  
Waldemar Karwowski ◽  
T. Plank ◽  
M. Parsaei ◽  
M. Rahimi
Keyword(s):  
Selection Process ◽  
Human Perception ◽  
Industrial Robots ◽  
Adjustment Process ◽  
Maximum Speed ◽  
Initial Speed ◽  
Robot Arm ◽  
Human Operators ◽  
Arm Motion ◽  
Assembly Tasks

A laboratory experiment was conducted to determine the maximum speeds of robot arm motion considered by the subjects as safe for human operators working in a close proximity of the robot's working envelope. Twenty-nine college students (16 males and 13 females) participated in the study as monitors of the simulated assembly tasks performed by two industrial robots of different size and work capabilities. The results show that the speed selection process depends on the robot's physical size and its initial speed at the start of the adjustment process. Subjects selected higher speeds as “safe” if they were first exposed to the maximum speed of the robot, and significantly lower values when the initial speed of the robot's actions was only 5% of maximum. It was also shown that the subject's previous exposure to robots and the level of their knowledge of industrial robots highly affected their perception of safe speeds of robot motions. Such effects differ, however, between males and females.

scholarly journals Classification of Drivers' Workload Using Physiological Signals in Conditional Automation

2021 ◽  
Vol 12 ◽  
Author(s):  
Quentin Meteier ◽  
Marine Capallera ◽  
Simon Ruffieux ◽  
Leonardo Angelini ◽  
Omar Abou Khaled ◽  
...  
Keyword(s):  
Secondary Task ◽  
Time Window ◽  
Mental Workload ◽  
Cognitive Task ◽  
Physiological Signals ◽  
Machine Learning Techniques ◽  
Physiological Data ◽  
Automated Driving ◽  
Physiological Indicators ◽  
High Level

The use of automation in cars is increasing. In future vehicles, drivers will no longer be in charge of the main driving task and may be allowed to perform a secondary task. However, they might be requested to regain control of the car if a hazardous situation occurs (i.e., conditionally automated driving). Performing a secondary task might increase drivers' mental workload and consequently decrease the takeover performance if the workload level exceeds a certain threshold. Knowledge about the driver's mental state might hence be useful for increasing safety in conditionally automated vehicles. Measuring drivers' workload continuously is essential to support the driver and hence limit the number of accidents in takeover situations. This goal can be achieved using machine learning techniques to evaluate and classify the drivers' workload in real-time. To evaluate the usefulness of physiological data as an indicator for workload in conditionally automated driving, three physiological signals from 90 subjects were collected during 25 min of automated driving in a fixed-base simulator. Half of the participants performed a verbal cognitive task to induce mental workload while the other half only had to monitor the environment of the car. Three classifiers, sensor fusion and levels of data segmentation were compared. Results show that the best model was able to successfully classify the condition of the driver with an accuracy of 95%. In some cases, the model benefited from sensors' fusion. Increasing the segmentation level (e.g., size of the time window to compute physiological indicators) increased the performance of the model for windows smaller than 4 min, but decreased for windows larger than 4 min. In conclusion, the study showed that a high level of drivers' mental workload can be accurately detected while driving in conditional automation based on 4-min recordings of respiration and skin conductance.

scholarly journals Problem solvers adjust cognitive offloading based on performance goals

2019 ◽  
Author(s):  
Patrick P. Weis ◽  
Eva Wiese
Keyword(s):  
Task Performance ◽  
Cognitive Processing ◽  
Mental Workload ◽  
Cognitive Task ◽  
Cognitive Strategies ◽  
Performance Goals ◽  
External Resource ◽  
Cognitive Offloading ◽  
Improved Performance ◽  
Problem Solvers

When incorporating the environment into mental processing (cf., cognitive offloading), one creates novel cognitive strategies that have the potential to improve task performance. Improved performance can, for example, mean faster problem solving, more accurate solutions, or even higher grades at university . Although cognitive offloading has frequently been associated with improved performance, it is yet unclear how flexible problem solvers are at matching their offloading habits with their current performance goals (can people improve goal-related instead of generic performance, e.g., when being in a hurry and aiming for a “quick and dirty” solution?). Here, we asked participants to solve a cognitive task, provided them with different goals – maximizing speed (SPD) or accuracy (ACC), respectively – and measured how frequently (Experiment 1) and how proficiently (Experiment 2) they made use of a novel external resource to support their cognitive processing. Experiment 1 showed that offloading behavior varied with goals: participants offloaded less in the SPD than in the ACC condition. Experiment 2 showed that this differential offloading behavior was associated with high goal-related performance: fast answers in the SPD, accurate answers in the ACC condition. Simultaneously, goal-unrelated performance was sacrificed: inaccurate answers in the SPD, slow answers in the ACC condition. The findings support the notion of humans as canny offloaders who are able to successfully incorporate their environment in pursuit of their current cognitive goals. Future efforts should be focused on the finding’s generalizability, e.g. to settings without feedback or with high mental workload.

Teacher improvement using a cognitive interaction analysis system

1985 ◽  
Vol 14 (1) ◽  
pp. 44-48
Author(s):  
D. M. Vietor ◽  
S. C. Brubaker ◽  
M. H. Milford ◽  
G. R. Johnson
Keyword(s):  
Interaction Analysis ◽  
Teacher Improvement ◽  
Cognitive Interaction ◽  
Analysis System

Eeg and Subjective Measures of Private Pilot Workload

1994 ◽  
Vol 38 (19) ◽  
pp. 1322-1325 ◽  
Author(s):  
Glenn F. Wilson ◽  
Thomas Hankins
Keyword(s):  
Performance Metrics ◽  
Mental Workload ◽  
Brain Wave ◽  
Subjective Data ◽  
Mental Demand ◽  
Psychophysiological Assessment ◽  
Human Operators ◽  
And Performance ◽  
Subjective Reports ◽  
Band Activity

Complex systems can place high levels of mental demand on human operators and methods of assessing these demands are needed. Subjective and performance metrics are typically employed while psychophysiological assessment has been used to a more limited extent. In this study, civilian pilots flew a single engine propeller aircraft on a flight profile designed to produce several levels of cognitive workload using VFR and IFR conditions. Subjective and brain wave (EEG) measures were used to assess mental workload. EEG theta band activity was sensitive to a wider range of workload levels and was more sensitive than the alpha and beta bands or the subjective reports. The alpha and beta bands reliably discriminated between ground and flight segments as did the subjective data.

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