scholarly journals Human-Robot-Interaction for mobile industrial robot teams

Procedia CIRP ◽  
2019 ◽  
Vol 79 ◽  
pp. 614-619 ◽  
Author(s):  
Julia Berg ◽  
Albrecht Lottermoser ◽  
Christoph Richter ◽  
Gunther Reinhart
Keyword(s):  
Industrial Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Robot Teams

scholarly journals Human–Robot Interaction through Eye Tracking for Artistic Drawing

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 54
Author(s):  
Lorenzo Scalera ◽  
Stefano Seriani ◽  
Paolo Gallina ◽  
Mattia Lentini ◽  
Alessandro Gasparetto
Keyword(s):  
Eye Tracking ◽  
Assistive Technology ◽  
Movement Disorders ◽  
Industrial Robot ◽  
Experimental Tests ◽  
Human Robot Interaction ◽  
Eye Tracker ◽  
Robot Interaction ◽  
Eye Motion ◽  
Artistic Images

In this paper, authors present a novel architecture for controlling an industrial robot via an eye tracking interface for artistic purposes. Humans and robots interact thanks to an acquisition system based on an eye tracker device that allows the user to control the motion of a robotic manipulator with his gaze. The feasibility of the robotic system is evaluated with experimental tests in which the robot is teleoperated to draw artistic images. The tool can be used by artists to investigate novel forms of art and by amputees or people with movement disorders or muscular paralysis, as an assistive technology for artistic drawing and painting, since, in these cases, eye motion is usually preserved.

The Pransky interview: Dr Cory Kidd, Founder and CEO at Catalia Health

2017 ◽  
Vol 44 (3) ◽  
pp. 259-263 ◽  
Author(s):  
Joanne Pransky
Keyword(s):  
Large Scale ◽  
Information Science ◽  
Industrial Robot ◽  
Human Robot Interaction ◽  
High Tech ◽  
Healthcare Applications ◽  
Robot Interaction ◽  
Wall Street ◽  
Content Type ◽  
Institute Of Technology

Purpose The purpose of this paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD-turned-entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market. Design/methodology/approach The interviewee is Dr Cory Kidd, an inventor, entrepreneur and leading practitioner in the field of human–robot interaction. Dr Kidd shares his 20-year journey of working at the intersection of healthcare and technology and how he applied innovative technologies toward solving large-scale consumer healthcare challenges. Findings Dr Kidd received his BS degree in Computer Science from the Georgia Institute of Technology and earned a National Science Foundation Graduate Research Fellow in Computer and Information Science & Engineering. Dr Kidd received his MS and PhD degrees at the MIT Media Lab in human–robot interaction. While there, he conducted studies that showed the psychological and clinical advantages of using a physical robot over screen-based interactions. While finishing his PhD in 2007, he founded his first company, Intuitive Automata, which created interactive coaches for weight loss. Though Intuitive Automata ceased operations in 2013, Dr Kidd harnessed his extensive knowledge of the healthcare business and the experiences from patient engagement and launched Catalia Health in 2014 with a new platform centered specifically around patient behavior change programs for chronic disease management. Originality/value Dr Kidd is a pioneer of social robotics and has developed groundbreaking technology for healthcare applications that combines artificial intelligence, psychology and medical best practices to deliver everyday care to patients who are managing chronic conditions. He holds patents, including one entitled Apparatus and Method for Assisting in Achieving Desired Behavior Patterns and in an Interactive Personal Health Promoting Robot. Dr Kidd was awarded the inaugural Wall Street Journal and Credit Suisse Technopreneur of the Year in 2010, which is meant to “honor the entry that best applies technology with the greatest potential for commercial success”. He is also the Director of Business Development for the nonprofit Silicon Valley Robotics and is an impact partner for Fresco Capital. He consults, mentors and serves as a Board Member and Advisor to several high-tech startups.

The Application and Extension of the Human-Animal Team Model to Better Understand Human-Robot Interaction: Recommendations for Further Research

2016 ◽  
Vol 60 (1) ◽  
pp. 1225-1229
Author(s):  
Katelynn A. Kapalo ◽  
Elizabeth Phillips ◽  
Stephen M. Fiore
Keyword(s):  
Social Interaction ◽  
Human Robot Interaction ◽  
Limited Capacity ◽  
Robot Interaction ◽  
Basic Framework ◽  
Robot Teams ◽  
Human Animal ◽  
Technological Constraints ◽  
Team Model ◽  
Research Recommendations

In order to create effective human-robot teams, robots must possess social capabilities that match the expectations of their human teammates. However the ability of robots to approximate human capacities is limited due to technological constraints. Human-animal teams have thus been suggested as a suitable analog for modeling teaming between humans and non-humans. Due to the limited capacity for animals to express their intentions, it follows that human-animal relationships can provide a basic framework for understanding how humans interpret information from teammates with limited social faculties. The purpose of this paper is provide research recommendations to identify specific areas in which human-animal teams can be used to model human-robot teams and to provide suggestions for investigating this model empirically in the context of social interaction.

Multimodal Feedback in Human-Robot Interaction

2016 ◽  
pp. 135-161
Author(s):  
Maria Vanessa aus der Wieschen ◽  
Kerstin Fischer ◽  
Kamil Kukliński ◽  
Lars Christian Jensen ◽  
Thiusius Rajeeth Savarimuthu
Keyword(s):  
Design Theory ◽  
Industrial Robot ◽  
Visual Presentation ◽  
Error Rates ◽  
Human Robot Interaction ◽  
Error Feedback ◽  
Robot Interaction ◽  
Multimodal Feedback ◽  
Feedback Modalities ◽  
The Many

A major area of interest within the fields of human-computer interaction (HCI) and human-robot interaction (HRI) is user feedback. Previous work in HCI has investigated the effects of error feedback on task efficiency and error rates, yet, these studies have been mostly restricted to comparisons of inherently different feedback modalities, for example auditory and visual, and as such fail to acknowledge the many possible variations within each of these modalities, some of which being more effective than others. This chapter applies a user-centered approach to investigating feedback modalities for robot teleoperation by naïve users. It identifies the reasons why novice users need feedback when demonstrating novel behaviors to a teleoperated industrial robot and evaluates both various feedback modalities designed to prevent errors and, drawing on document design theory, studies different kinds of visual presentation regarding their effectiveness in the creation of legible error feedback screens.

Practical application of a safe human-robot interaction software

2020 ◽  
Vol 47 (3) ◽  
pp. 359-368 ◽  
Author(s):  
Mustafa Can Bingol ◽  
Omur Aydogmus
Keyword(s):  
Robot Manipulator ◽  
Industrial Robot ◽  
Wavelet Packet ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Robot Interaction ◽  
Content Type ◽  
Depth Sensors ◽  
Working Space ◽  
Vision Module

Purpose Because of the increased use of robots in the industry, it has become inevitable for humans and robots to be able to work together. Therefore, human security has become the primary noncompromising factor of joint human and robot operations. For this reason, the purpose of this study was to develop a safe human-robot interaction software based on vision and touch. Design/methodology/approach The software consists of three modules. Firstly, the vision module has two tasks: to determine whether there is a human presence and to measure the distance between the robot and the human within the robot’s working space using convolutional neural networks (CNNs) and depth sensors. Secondly, the touch detection module perceives whether or not a human physically touches the robot within the same work environment using robot axis torques, wavelet packet decomposition algorithm and CNN. Lastly, the robot’s operating speed is adjusted according to hazard levels came from vision and touch module using the robot’s control module. Findings The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error. Practical implications The success of the developed algorithm was demonstrated in the current study and the algorithm can be used in other industrial robots for safety. Originality/value In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.

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