Designing a Multimodal Human-Robot Interaction Interface for an Industrial Robot

2015 ◽  
pp. 255-263
Author(s):  
Bogdan Mocan ◽  
Mircea Fulea ◽  
Stelian Brad
Keyword(s):  
Industrial Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Interaction Interface

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.

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.

scholarly journals An Augmented Reality Based Human-Robot Interaction Interface Using Kalman Filter Sensor Fusion

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4586 ◽  
Author(s):  
Chunxu Li ◽  
Ashraf Fahmy ◽  
Johann Sienz
Keyword(s):  
Kalman Filter ◽  
Augmented Reality ◽  
Sensor Fusion ◽  
Kalman Filtering ◽  
Control Process ◽  
Human Robot Interaction ◽  
Post Processing ◽  
Robot Interaction ◽  
Kinect Camera ◽  
Interaction Interface

In this paper, the application of Augmented Reality (AR) for the control and adjustment of robots has been developed, with the aim of making interaction and adjustment of robots easier and more accurate from a remote location. A LeapMotion sensor based controller has been investigated to track the movement of the operator hands. The data from the controller allows gestures and the position of the hand palm’s central point to be detected and tracked. A Kinect V2 camera is able to measure the corresponding motion velocities in x, y, z directions after our investigated post-processing algorithm is fulfilled. Unreal Engine 4 is used to create an AR environment for the user to monitor the control process immersively. Kalman filtering (KF) algorithm is employed to fuse the position signals from the LeapMotion sensor with the velocity signals from the Kinect camera sensor, respectively. The fused/optimal data are sent to teleoperate a Baxter robot in real-time by User Datagram Protocol (UDP). Several experiments have been conducted to test the validation of the proposed method.

scholarly journals Dynamic and Friction Parameters of an Industrial Robot: Identification, Comparison and Repetitiveness Analysis

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 49
Author(s):  
Lei Hao ◽  
Roberto Pagani ◽  
Manuel Beschi ◽  
Giovanni Legnani
Keyword(s):  
Industrial Robot ◽  
Human Robot Interaction ◽  
Dynamic Tests ◽  
Dynamics Model ◽  
Robot Interaction ◽  
Joint Friction ◽  
Industrial Manipulator ◽  
Exponential Law ◽  
Double Exponential ◽  
Friction Parameters

This paper describes the results of dynamic tests performed to study the robustness of a dynamics model of an industrial manipulator. The tests show that the joint friction changes during the robot operation. The variation can be identified in a double exponential law and thus the variation can be predicted. The variation is due to the heat generated by the friction. A model is used to estimate the temperature and related friction variation. Experimental data collected on two robots EFORT ER3A-C60 are presented and discussed. Repetitive tests performed on different days showed that the inertial and friction parameters can be robustly estimated and that the value of the measured joint friction can be used to estimate the unexpected conditions of the joints. Future applications may include sensorless identification of collisions, predictive maintenance programs, or human–robot interaction.

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