Welcome to the

HUman-MAchines INteraction Laboratory (HUMAIN-Lab)

Welcome to the

HUman-MAchines INteraction Laboratory (HUMAIN-Lab)

Scope:
Machines, implemented either in hardware or in software, with whom a human interacts proliferate, furthermore their complexity increases; for instance, the aforementioned machines include devices for communication, computers, robots, costumer service software, and other. This lab pursues the study, analysis and design of both hardware and software that enables the seamless collaboration of humans with machines.
Objectives

Innovation

The operation of a machine in the “physical” environment is typically supported by arithmetic models. However, when a human is involved there might emerge non-numerical data…

Inventiveness

Our orientation is toward the development of machines with a capacity to interact with humans in various applications including education, precision farming, patrolling in the physical environment and other.

Entrepreneurship

Our orientation is toward the conversion of our laboratory prototypes in commercial products.

Vassilis Kaburlasos

Expertise: Computational Intelligence
Homepage

Theodoros Pachidis

Expertise: Robotics and Software Engineering

Michail Manios

Technical Staff
Homepage

Stamatis Chatzistamatis

Administrative Staff

Effectiveness of a robot-assisted psychological intervention for children with autism spectrum disorder – Journal of Autism and Developmental Disorders

Abstract Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The main aim of this randomised controlled study was to evaluate the effectiveness of a robot-assisted psychosocial intervention and the secondary aim was to investigate potential differences between a robot-assisted intervention group and a control group receiving intervention by humans only. The analysis of the results showed…

0
Read More

Social robots for pedagogical rehabilitation in special education for the elderly – V-RITA2022

Abstract Numerous studies have reported social robot applications for children including both typical and special education. Similar applications for the elderly are underplayed. However, children grow to adults and, ultimately, to elderly. This preliminary work, based on our expertise with social robot NAO in special education applications for children, reports an approach for engaging social robots for elderly with Alzheimer’s disease. In particular, a social robot, equipped with a variety of electronic sensors and supported by suitable mathematical models implemented in software, is engaged as a…

0
Read More

Considerations for a multi-purpose agrobot design toward automating skillful viticultural tasks: a study in northern Greece vineyards – HAICTA 2022, Athens, Greece

Abstract Seasonal labor shortages in agriculture are experienced throughout Europe and beyond especially, but not only, during the harvest time when the demand for hands is high as well as urgent. Agrobots have been established as a sustainable solution to support these growing demands due to their capacity to work incessantly, fast as well as with skillful precision.  In the aforementioned context, this work investigates the design of a single multi-purpose robotic system towards automation of a number of skillful…

0
Read More

Variable selection for the prediction of TSS, pH and TA of intact berries of Thompson seedless grapes from their NIS reflection – SoftCOM 2022, Split, Croatia

Abstract Wavenumbers of high absolute value of correlation coefficient to Total Soluble Solids (TSS), pH, or Titratable Acidity (TA) were selected from reflection Fourier transform near infrared (FT-NIR) spectra of intact grape berries of the white variety Thompson Seedless. Multiple linear regression (MLR) and partial least squares (PLS) regression were applied to the spectra to construct trained regression models able to predict TSS, pH, and TA. Square Pearson’s correlation coefficient (R2) and the Mean Square Error (MSE) were used to…
0
Read More

Variable Selection on Reflectance NIR Spectra for the Prediction of TSS in Intact Berries of Thompson Seedless Grapes – Agronomy 2022, vol. 12, no. 9, 2113

Abstract Fourier-transform near infrared (FT-NIR) reflection spectra of intact berries of the grape variety Thompson seedless were used to predict total soluble solids (TSS) content. From an initial dataset, 12 subsets were considered by applying variable selection to extract the reflectance values at wavenumbers most correlated to the chemometrically measured TSS content. The datasets were processed by both multiple linear regression (MLR) and partial least squares (PLS) methods towards predicting the TSS content from the reflection values of each spectrum.…

0
Read More