Robotic Finishing of Interior Regions of Geometrically Complex Parts

2018 ◽  
Author(s):  
Ariyan M. Kabir ◽  
Aniruddha V. Shembekar ◽  
Rishi K. Malhan ◽  
Rohil S. Aggarwal ◽  
Joshua D. Langsfeld ◽  
...  
Keyword(s):  
Human Operator ◽  
Surface Finishing ◽  
Complex Geometries ◽  
Task Requirements ◽  
Planning Algorithm ◽  
Human Operators ◽  
High Level ◽  
Complex Parts ◽  
Programming Time ◽  
And Task

Surface finishing is an important manufacturing process. Many parts with complex geometries require finishing of internal regions before they can be used. In small and medium volume productions most of the finishing tasks are non-repetitive in nature, and have to be performed manually. These finishing operations for parts with complex geometries can be quite labor intensive, and may pose risk to humans. We have developed a collaborative finishing system where human operators work on high level decision making, and the robot assistants carry out the labor intensive low level finishing tasks. The human operator guides the robotic system by transferring operator knowledge through a user interface. Our system generates instructions for the robots based on the user inputs and task requirements. We have also developed a planning algorithm that automatically computes the paths for the robots by using the CAD model of the part. This significantly reduces the robot programming time and improves the efficiency of the finishing system. If needed, the system seeks help from the human operator by generating notifications.

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

A Meta-Mining Ontology Framework for Data Processing

2021 ◽  
Vol 12 (2) ◽  
pp. 37-56
Author(s):  
Man Tianxing ◽  
Nataly Zhukova ◽  
Alexander Vodyaho ◽  
Tin Tun Aung
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
Data Streams ◽  
Specific Data ◽  
Ontology Merging ◽  
Knowledge Models ◽  
Task Requirements ◽  
Ontology Extraction ◽  
Merging Method ◽  
And Task

Extracting knowledge from data streams received from observed objects through data mining is required in various domains. However, there is a lack of any kind of guidance on which techniques can or should be used in which contexts. Meta mining technology can help build processes of data processing based on knowledge models taking into account the specific features of the objects. This paper proposes a meta mining ontology framework that allows selecting algorithms for solving specific data mining tasks and build suitable processes. The proposed ontology is constructed using existing ontologies and is extended with an ontology of data characteristics and task requirements. Different from the existing ontologies, the proposed ontology describes the overall data mining process, used to build data processing processes in various domains, and has low computational complexity compared to others. The authors developed an ontology merging method and a sub-ontology extraction method, which are implemented based on OWL API via extracting and integrating the relevant axioms.

The Effects of Stimulus and Response Modalities and Task Loading on Dual-Task Performance

1978 ◽  
Vol 22 (1) ◽  
pp. 182-182
Author(s):  
Steven D. Harris ◽  
Jerry M. Owens ◽  
Robert A. North
Keyword(s):  
New Technology ◽  
Speech Understanding ◽  
Military Aircraft ◽  
Significant Progress ◽  
Dual Task Performance ◽  
Artificial Intelligence Technology ◽  
Military Systems ◽  
High Level ◽  
Computer Recognition ◽  
And Task

Recent advances in artificial intelligence technology have resulted in commercially available computer systems that are able to synthesize auditory messages and to recognize spoken words and phrases in near-real-time with a high level of reliability. Several researchers have enumerated the benefits that are expected to accrue from computer recognition of speech (1971, 1975). Beek, Neuberg, and Hodge (1977) summarized the possible applications of this new technology to military systems. Curran (1978) and Coler, Plummer, Huff and Hitchcock (1978) reported significant progress in the development of automated speech understanding systems for the control of on-board systems in military aircraft.

scholarly journals Bringing the Leader Back in: Why, How, and When Leadership Empowerment Behavior Shapes Coworker Conflict

2020 ◽  
Vol 45 (5) ◽  
pp. 599-636 ◽  
Author(s):  
Mladen Adamovic ◽  
Peter Gahan ◽  
Jesse E. Olsen ◽  
Bill Harley ◽  
Joshua Healy ◽  
...  
Keyword(s):  
Task Conflict ◽  
Relationship Conflict ◽  
Cognitive Trust ◽  
Trust In Leaders ◽  
Negative Effect ◽  
Role Description ◽  
High Level ◽  
Organizational Hierarchies ◽  
Conflict Research ◽  
And Task

With the diffusion of team-based work organizations and flatter organizational hierarchies, many leaders empower employees to perform their work. Empowerment creates an interesting tension regarding coworker conflict, enhancing trust and giving employees more autonomy to prevent conflict, while also increasing workload and the potential for coworker conflict. Recent conflict research has focused on how characteristics of individuals, groups, and tasks contribute to conflict among coworkers. We extend this work by exploring the role of leader empowerment behavior (LEB) in influencing coworker conflict. Our model integrates research on LEB and coworker conflict to help organizations manage coworker conflict effectively. To test our model at the workplace level, we utilize data drawn from matched surveys of leaders and employees in 317 workplaces. We find that LEB relates negatively to relationship and task conflict through affective and cognitive trust in leaders. We further find that LEB relates negatively to relationship and task conflict through reduced workload, but only when employees have a clear role description. In contrast, if employees have unclear roles, LEB has a U-curve relationship with workload: a moderate level of LEB reduces workload, but a high level of LEB increases workload, in turn increasing coworker conflict. Finally, relationship conflict has a direct negative effect on task performance, whereas task conflict has an indirect negative effect through relationship conflict.

Collaborative Autonomy between High-level Behaviors and Human Operators for Remote Manipulation Tasks using Different Humanoid Robots

2016 ◽  
Vol 34 (2) ◽  
pp. 333-358 ◽  
Author(s):  
Alberto Romay ◽  
Stefan Kohlbrecher ◽  
Alexander Stumpf ◽  
Oskar von Stryk ◽  
Spyros Maniatopoulos ◽  
...  
Keyword(s):  
Humanoid Robots ◽  
Remote Manipulation ◽  
Human Operators ◽  
High Level ◽  
Collaborative Autonomy

Effects of Working Memory Capacity, Task Switching, and Task Difficulty on Multitasking Performance

2016 ◽  
Vol 60 (1) ◽  
pp. 502-506 ◽  
Author(s):  
Shijing Liu ◽  
Amy Wadeson ◽  
Na Young Kim ◽  
Chang S. Nam
Keyword(s):  
Working Memory ◽  
Task Switching ◽  
Task Difficulty ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Trail Making ◽  
Human Operators ◽  
Switching Task ◽  
Different Levels ◽  
And Task

Multitasking requires human operators to handle the demands of multiple tasks through task switching at the same time and this ability is required in many jobs. Previous studies showed that different levels of working memory capacity (WMC) and task switching abilities can lead to differences on multitasking performance. With increased complexity of tasks, maintaining task performance is challenging. This study sought to find the relations of WMC, task switching, task difficulty, and multitasking performance. Multi-Attribute Task Battery II (MATB-II) was employed in this study as a platform to assess multitasking. Automated OSPAN and Trail Making Tasks (TMT) were used to assess WMC and the task switching ability, respectively. Results indicated that there were significant effects of these three parameters on multitasking performance. Other dimensions of multitasking performance will be addressed in future studies.

Brain Computer Interface Robotic Co-Workers: Defective Part Picking System

2018 ◽  
Author(s):  
Yao Li ◽  
Thenkurussi Kesavadas
Keyword(s):  
Direct Instruction ◽  
Human Subject ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Human Operator ◽  
Human Being ◽  
Unstructured Environment ◽  
Human Operators ◽  
Application Fields ◽  
Picking System

Industrial robotic co-workers are robots that can work with human being in an unstructured environment. Such robots, must be able to assist human operators in a seamless way without receiving specific instructions. Robotic co-workers can open entirely new application fields in manufacturing as demonstrated in this paper. We designed such an industrial co-robot to pick up defective parts by simply monitoring a human operator directly through a brain computer interface (BCI). By constantly monitoring the operator using BCI sensors, the robotic co-worker can sense when an operator notices a defective part and then moves to remove the part from a moving conveyor with no direct instruction from the operator. The robot, equipped with an RGB camera, recognizes the part, tracks the position and generates accurate motion plan. We demonstrated the system using a human subject study.

Task allocation for improved ergonomics in Human-Robot Collaborative Assembly

2019 ◽  
Vol 20 (1) ◽  
pp. 102-133 ◽  
Author(s):  
Ilias El Makrini ◽  
Kelly Merckaert ◽  
Joris De Winter ◽  
Dirk Lefeber ◽  
Bram Vanderborght
Keyword(s):  
Task Allocation ◽  
Health Concern ◽  
Production Environment ◽  
Task Requirements ◽  
Collaborative Assembly ◽  
Agent Characteristics ◽  
Human Robot Collaboration ◽  
Collaborative Robot ◽  
And Task

Abstract Human-robot collaboration, whereby the human and the robot join their forces to achieve a task, opens new application opportunities in manufacturing. Robots can perform precise and repetitive operations while humans can execute tasks that require dexterity and problem-solving abilities. Moreover, collaborative robots can take over heavy-duty tasks. Musculoskeletal disorders (MSDs) are a serious health concern and the primary cause of absenteeism at work. While the role of the human is still essential in flexible production environment, the robot can help decreasing the workload of workers. This paper describes a novel framework for task allocation of human-robot assembly applications based on capabilities and ergonomics considerations. Capable agents are determined on the basis of agent characteristics and task requirements. Ergonomics is integrated by measuring the human body posture and the related workload. The developed framework was validated on a gearbox assembly use case using the collaborative robot Baxter.

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