An improved background subtraction method for HRI based on image parameters

Kybernetes ◽  
2014 ◽  
Vol 43 (7) ◽  
pp. 1003-1023
Author(s):  
Qiongxiong Ma ◽  
Tie Zhang
Keyword(s):  
Background Subtraction ◽  
Human Robot Interaction ◽  
Background Model ◽  
Foreground Detection ◽  
Threshold Values ◽  
Subtraction Method ◽  
Robot Interaction ◽  
Content Type ◽  
Previous Image ◽  
Selection Of

Purpose – Background subtraction is a particularly popular foreground detection method, whose background model can be updated by using input images. However, foreground object cannot be detected accurately if the background model is broken. In order to improve the performance of foreground detection in human-robot interaction (HRI), the purpose of this paper is to propose a new background subtraction method based on image parameters, which helps to improve the robustness of the existing background subtraction method. Design/methodology/approach – The proposed method evaluates the image and foreground results according to the image parameters representing the change features of the image. It ignores the image that is similar to the first image and the previous image in image sequence, filters the image that may break the background model and detects the abnormal background model. The method also helps to rebuild the background model when the model is broken. Findings – Experimental results of typical interaction scenes validate that the proposed method helps to reduce the broken probability of background model and improve the robustness of background subtraction. Research limitations/implications – Different threshold values of image parameters may affect the results in different environments. Future researches should focus on the automatic selection of parameters’ threshold values according to the interaction scene. Practical implications – A useful method for foreground detection in HRI. Originality/value – This paper proposes a method which employs image parameters to improve the robustness of the background subtraction for foreground detection in HRI.

AI and libraries: trends and projections

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Adetoun A. Oyelude
Keyword(s):  
Language Processing ◽  
Service Provision ◽  
Design Methodology ◽  
Human Robot Interaction ◽  
Human Intelligence ◽  
Library Service ◽  
Robot Interaction ◽  
Content Type ◽  
New Horizons ◽  
Advanced Technologies

Purpose This paper aims to focus on the trends and projection for future use of artificial intelligence (AI) in libraries. AI technologies is the latest among the technologies being used in libraries. The technology has systems that have natural language processing, machine learning and pattern recognition capabilities that make service provision easier for libraries. Design/methodology/approach Systematic literature review is done, exploring blogs and wikis, to collect information on the ways in which AI is used and can be futuristically used in libraries. Findings This paper found that uses of AI in libraries entailed enhanced services such as content indexing, document matching, content mapping content summarization and many others. AI possibilities were also found to include improving the technology of gripping, localizing and human–robot interaction and also having artificial superintelligence, the hypothetical AI that surpasses human intelligence and abilities. Originality/value It is concluded that advanced technologies that AI are, will help librarians to open up new horizons and solve challenges that crop up in library service delivery.

Affective Goal and Task Selection for Social Robots

2009 ◽  
pp. 74-87 ◽  
Author(s):  
Matthias Scheutz ◽  
Paul Schermerhorn
Keyword(s):  
Decision Making ◽  
Real World ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Task Selection ◽  
Resource Limitations ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Selection Of

Effective decision-making under real-world conditions can be very difficult as purely rational methods of decision-making are often not feasible or applicable. Psychologists have long hypothesized that humans are able to cope with time and resource limitations by employing affective evaluations rather than rational ones. In this chapter, we present the distributed integrated affect cognition and reflection architecture DIARC for social robots intended for natural human-robot interaction and demonstrate the utility of its human-inspired affect mechanisms for the selection of tasks and goals. Specifically, we show that DIARC incorporates affect mechanisms throughout the architecture, which are based on “evaluation signals” generated in each architectural component to obtain quick and efficient estimates of the state of the component, and illustrate the operation and utility of these mechanisms with examples from human-robot interaction experiments.

Block Background Subtraction Method Based on ViBe

2014 ◽  
Vol 556-562 ◽  
pp. 3549-3552
Author(s):  
Lian Fen Huang ◽  
Qing Yue Chen ◽  
Jin Feng Lin ◽  
He Zhi Lin
Keyword(s):  
Spatial Correlation ◽  
Background Subtraction ◽  
Video Sequence ◽  
Moving Objects ◽  
Moving Object ◽  
Background Model ◽  
Subtraction Method ◽  
Current Frame ◽  
The Difference ◽  
Set Up

The key of background subtraction which is widely used in moving object detecting is to set up and update the background model. This paper presents a block background subtraction method based on ViBe, using the spatial correlation and time continuity of the video sequence. Set up the video sequence background model firstly. Then, update the background model through block processing. Finally employ the difference between the current frame and background model to extract moving objects.

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.

Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: a case study using low cost sensors

Sensor Review ◽  
2015 ◽  
Vol 35 (3) ◽  
pp. 244-250 ◽  
Author(s):  
Pedro Neto ◽  
Nuno Mendes ◽  
A. Paulo Moreira
Keyword(s):  
Kalman Filter ◽  
Inertial Sensor ◽  
Low Cost ◽  
Human Robot Interaction ◽  
Magnetic Sensor ◽  
Robot Interaction ◽  
Magnetic Sensing ◽  
Content Type ◽  
Reliable Estimation ◽  
Yaw Angle

Purpose – The purpose of this paper is to achieve reliable estimation of yaw angles by fusing data from low-cost inertial and magnetic sensing. Design/methodology/approach – In this paper, yaw angle is estimated by fusing inertial and magnetic sensing from a digital compass and a gyroscope, respectively. A Kalman filter estimates the error produced by the gyroscope. Findings – Drift effect produced by the gyroscope is significantly reduced and, at the same time, the system has the ability to react quickly to orientation changes. The system combines the best of each sensor, the stability of the magnetic sensor and the fast response of the inertial sensor. Research limitations/implications – The system does not present a stable behavior in the presence of large vibrations. Considerable calibration efforts are needed. Practical implications – Today, most of human–robot interaction technologies need to have the ability to estimate orientation, especially yaw angle, from small-sized and low-cost sensors. Originality/value – Existing methods for inertial and magnetic sensor fusion are combined to achieve reliable estimation of yaw angle. Experimental tests in a human–robot interaction scenario show the performance of the system.

Impedance control of a cable-driven SEA with mixed H2/H∞ synthesis

2017 ◽  
Vol 37 (3) ◽  
pp. 296-303 ◽  
Author(s):  
Ningbo Yu ◽  
Wulin Zou
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Impedance Control ◽  
Low Frequency ◽  
Human Robot Interaction ◽  
Control Input ◽  
Robot Interaction ◽  
Content Type ◽  
Series Elastic Actuator ◽  
Series Elastic

Purpose This paper aims to present an impedance control method with mixed H2/H∞ synthesis and relaxed passivity for a cable-driven series elastic actuator to be applied for physical human–robot interaction. Design/methodology/approach To shape the system’s impedance to match a desired dynamic model, the impedance control problem was reformulated into an impedance matching structure. The desired competing performance requirements as well as constraints from the physical system can be characterized with weighting functions for respective signals. Considering the frequency properties of human movements, the passivity constraint for stable human–robot interaction, which is required on the entire frequency spectrum and may bring conservative solutions, has been relaxed in such a way that it only restrains the low frequency band. Thus, impedance control became a mixed H2/H∞ synthesis problem, and a dynamic output feedback controller can be obtained. Findings The proposed impedance control strategy has been tested for various desired impedance with both simulation and experiments on the cable-driven series elastic actuator platform. The actual interaction torque tracked well the desired torque within the desired norm bounds, and the control input was regulated below the motor velocity limit. The closed loop system can guarantee relaxed passivity at low frequency. Both simulation and experimental results have validated the feasibility and efficacy of the proposed method. Originality/value This impedance control strategy with mixed H2/H∞ synthesis and relaxed passivity provides a novel, effective and less conservative method for physical human–robot interaction control.

Improving stability in physical human–robot interaction by estimating human hand stiffness and a vibration index

2019 ◽  
Vol 46 (4) ◽  
pp. 529-540 ◽  
Author(s):  
Feifei Bian ◽  
Danmei Ren ◽  
Ruifeng Li ◽  
Peidong Liang
Keyword(s):  
Time Delay ◽  
Real Time ◽  
Time Domain ◽  
Design Methodology ◽  
Interaction Force ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
Human Hand ◽  
Robot Interaction ◽  
Content Type

Purpose The purpose of this paper is to eliminate instability which may occur when a human stiffens his arms in physical human–robot interaction by estimating the human hand stiffness and presenting a modified vibration index. Design/methodology/approach Human hand stiffness is first estimated in real time as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A time-domain vibration index based on the interaction force is then modified to reduce the delay in instability detection. The instability is confirmed when the vibration index exceeds a given threshold. The virtual damping coefficient in admittance controller is adjusted accordingly to ensure stability in physical human–robot interaction. Findings By estimating the human hand stiffness and modifying the vibration index, the instability which may occur in stiff environment in physical human–robot interaction is detected and eliminated, and the time delay is reduced. The experimental results demonstrate significant improvement in stabilizing the system when the human operator stiffens his arms. Originality/value The originality is in estimating the human hand stiffness online as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A modification of the vibration index is also an originality to reduce the time delay of instability detection.

Human robot interaction for manipulation tasks based on stroke gesture recognition

2017 ◽  
Vol 44 (6) ◽  
pp. 700-710 ◽  
Author(s):  
Jiajun Li ◽  
Jianguo Tao ◽  
Liang Ding ◽  
Haibo Gao ◽  
Zongquan Deng ◽  
...  
Keyword(s):  
Gesture Recognition ◽  
Design Methodology ◽  
Spatial Information ◽  
Recognition Accuracy ◽  
Parameter Extraction ◽  
Human Robot Interaction ◽  
Extraction System ◽  
Robot Interaction ◽  
Content Type ◽  
Practical Implications

Purpose The purpose of this paper is to extend the usage of stroke gestures in manipulation tasks to make the interaction between human and robot more efficient. Design/methodology/approach In this paper, a set of stroke gestures is designed for typical manipulation tasks. A gesture recognition and parameter extraction system is proposed to exploit the information in stroke gestures drawn by the users. Findings The results show that the designed gesture recognition subsystem can reach a recognition accuracy of 99.00 per cent. The parameter extraction subsystem can successfully extract parameters needed for typical manipulation tasks with a success rate about 86.30 per cent. The system shows an acceptable performance in the experiments. Practical implications Using stroke gesture in manipulation tasks can make the transmission of human intentions to the robots more efficient. The proposed gesture recognition subsystem is based on convolutional neural network which is robust to different input. The parameter extraction subsystem can extract the spatial information encoded in stroke gestures. Originality/value The author designs stroke gestures for manipulation tasks which is an extension of the usage of stroke gestures. The proposed gesture recognition and parameter extraction system can make use of stroke gestures to get the type of the task and important parameters for the task simultaneously.

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.

An angle-changeable tracked robot with human-robot interaction in unstructured environments

2020 ◽  
Vol 40 (4) ◽  
pp. 565-575
Author(s):  
Chengguo Zong ◽  
Zhijian Ji ◽  
Junzhi Yu ◽  
Haisheng Yu
Keyword(s):  
Control System ◽  
Design Method ◽  
Static Stability ◽  
Human Robot Interaction ◽  
Working Environment ◽  
Robot Interaction ◽  
Content Type ◽  
Mechanical Structure ◽  
Rugged Terrain ◽  
Interaction Control

Purpose The purpose of this paper is to study the adaptability of the tracked robot in complex working environment. It proposes an angle-changeable tracked robot with human–robot interaction in unstructured environment. The study aims to present the mechanical structure and human–robot interaction control system of the tracked robot and analyze the static stability of the robot working in three terrains, i.e. rugged terrain, sloped terrain and stairs. Design/methodology/approach The paper presents the mechanical structure and human–robot interaction control system of the tracked robot. To prevent the detachment of the tracks during obstacle navigation, a new type of passively adaptive device based on the relationship between the track’s variable angle and the forces is presented. Then three types of rough terrain are chosen to analyze the static stability of the tracked robot, i.e. rugged terrain, sloped terrain and stairs. Findings This paper provides the design method of the tracked robot. Owing to its appropriate dimensions, good mass distribution and limited velocity, the tracked robot remains stable on the complex terrains. The experimental results verify the effectiveness of the design method. Originality/value The theoretical analysis of this paper provides basic reference for the structural design of tracked robots.

Sign in / Sign up

Export Citation Format

Share Document