Object Recognition Pipeline

Advancements in Computer Vision and Image Processing - Advances in Computer and Electrical Engineering ◽

10.4018/978-1-5225-5628-2.ch002 ◽

2018 ◽

pp. 18-33

Author(s):

John Alejandro Castro Vargas ◽

Alberto Garcia Garcia ◽

Sergiu Oprea ◽

Sergio Orts Escolano ◽

Jose Garcia Rodriguez

Keyword(s):

Object Recognition ◽

Real Time ◽

Social Robots ◽

Social Robot ◽

Degree Of Disability ◽

Domestic Environments ◽

Domestic Assistance

Object grasping in domestic environments using social robots has an enormous potential to help dependent people with a certain degree of disability. In this chapter, the authors make use of the well-known Pepper social robot to carry out such task. They provide an integrated solution using ROS to recognize and grasp simple objects. That system was deployed on an accelerator platform (Jetson TX1) to be able to perform object recognition in real time using RGB-D sensors attached to the robot. By using the system, the authors prove that the Pepper robot shows a great potential for such domestic assistance tasks.

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Object Recognition Pipeline

Rapid Automation ◽

10.4018/978-1-5225-8060-7.ch021 ◽

2019 ◽

pp. 456-468

Author(s):

John Alejandro Castro Vargas ◽

Alberto Garcia Garcia ◽

Sergiu Oprea ◽

Sergio Orts Escolano ◽

Jose Garcia Rodriguez

Keyword(s):

Object Recognition ◽

Real Time ◽

Social Robots ◽

Social Robot ◽

Degree Of Disability ◽

Domestic Environments ◽

Domestic Assistance

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Augmented Reality Maintenance Assistant Using YOLOv5

Applied Sciences ◽

10.3390/app11114758 ◽

2021 ◽

Vol 11 (11) ◽

pp. 4758

Author(s):

Ana Malta ◽

Mateus Mendes ◽

Torres Farinha

Keyword(s):

Neural Network ◽

Deep Learning ◽

Object Recognition ◽

Augmented Reality ◽

Real Time ◽

Recognition System ◽

High Accuracy ◽

Video Streams ◽

The Neural Network ◽

Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

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Mitigating Children’s Pain and Anxiety during Blood Draw Using Social Robots

Electronics ◽

10.3390/electronics10101211 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1211

Author(s):

Matthijs H. J. Smakman ◽

Koen Smit ◽

Lotte Buser ◽

Tom Monshouwer ◽

Nigel van Putten ◽

...

Keyword(s):

Healthcare Professionals ◽

Young Patients ◽

Hospital Setting ◽

Social Robots ◽

Social Robot ◽

Blood Collection ◽

Medical Procedure ◽

Blood Draw ◽

The Social ◽

Children's Pain

Young pediatric patients who undergo venipuncture or capillary blood sampling often experience high levels of pain and anxiety. This often results in distressed young patients and their parents, increased treatment times, and a higher workload for healthcare professionals. Social robots are a new and promising tool to mitigate children’s pain and anxiety. This study aims to purposefully design and test a social robot for mitigating stress and anxiety during blood draw of children. We first programmed a social robot based on the requirements expressed by experienced healthcare professionals during focus group sessions. Next, we designed a randomized controlled experiment in which the social robot was applied as a distraction method to measure its capacity to mitigate pain and anxiety in children during blood draw in a children’s hospital setting. Children who interacted with the robot showed significantly lower levels of anxiety before actual blood collection, compared to children who received regular medical treatment. Children in the middle classes of primary school (aged 6–9) seemed especially sensitive to the robot’s ability to mitigate pain and anxiety before blood draw. Children’s parents overall expressed strong positive attitudes toward the use and effectiveness of the social robot for mitigating pain and anxiety. The results of this study demonstrate that social robots can be considered a new and effective tool for lowering children’s anxiety prior to the distressing medical procedure of blood collection.

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The Social Robot in Rehabilitation and Assistance: What is the Future?

Healthcare ◽

10.3390/healthcare9030244 ◽

2021 ◽

Vol 9 (3) ◽

pp. 244

Author(s):

Daniele Giansanti

Keyword(s):

The Elderly ◽

Social Robots ◽

Social Robot ◽

Clinical Use ◽

Research Development ◽

Future Directions ◽

Collaborative Robotics ◽

Research Perspectives ◽

The Social ◽

The Future

This commentary aims to address the field of social robots both in terms of the global situation and research perspectives. It has four polarities. First, it revisits the evolutions in robotics, which, starting from collaborative robotics, has led to the diffusion of social robots. Second, it illustrates the main fields in the employment of social robots in rehabilitation and assistance in the elderly and handicapped and in further emerging sectors. Third, it takes a look at the future directions of the research development both in terms of clinical and technological aspects. Fourth, it discusses the opportunities and limits, starting from the development and clinical use of social robots during the COVID-19 pandemic to the increase of ethical discussion on their use.

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