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Sensors and Sensing Technologies for Social Robots

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 1049

Special Issue Editors


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Guest Editor
Department of Electronic Technology, University of Málaga, Campus de Teatinos, 29071 Málaga, Spain
Interests: social robotics; artificial vision; autonomous robots; human-robot interaction; social navigation; pose analysis; gesture recognition
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computing Science, Umeå Universitetdisabled, 90187 Umea, Sweden
Interests: social robots; artificial vision; smart environments
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent technological advances have made it possible to initiate a progressive deployment of service robots in daily life contexts. These next-generation robots are connected to smart environments and other agents, rely on artificial intelligence-based solutions to interact with people using natural channels and cooperate with humans and other agents to accomplish different tasks.

Robots working in these settings must be aware of their context, not only physical but also social. They need to perceive, understand, and adapt their behavior to this context, with special emphasis on perceiving and predicting people’s activities. New sensors and combinations of sensors are employed to help with achieving these tasks, ranging from multicamera systems to radar-based person recognizers, considering both sensors mounted on the robot and others located in the environment or in other agents. The nature and characteristics of these sensors are also influenced by the application domain in which the robot is deployed, ranging from industrial co-workers to home assistants.

In addition to new sensing approaches, Vision–Language Models (VLMs) have emerged as powerful tools for perception, enabling robots to process and interpret complex visual input.

We invite contributions on novel methods, applications, and developments integrating VLMs, advanced sensing techniques, and AI-based solutions for social robots. Topics include, but are not limited to, the following:

  • Artificial vision systems;
  • Person activity recognition;
  • Remote person monitoring sensors;
  • Sensors for socially assistive robots;
  • Multimodal sensor fusion;
  • FPGA- and ASIC-based sensor solutions for social robots.

Prof. Dr. Juan Pedro Bandera
Dr. Suna Bensch
Guest Editors

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Keywords

  • social robots
  • sensor fusion
  • artificial vision
  • object detection
  • activity recognition
  • human–robot interaction
  • shared perception
  • multiagent cooperation

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Published Papers (1 paper)

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Research

31 pages, 5071 KB  
Article
Feasibility of an AI-Enabled Smart Mirror Integrating MA-rPPG, Facial Affect, and Conversational Guidance in Realtime
by Mohammad Afif Kasno and Jin-Woo Jung
Sensors 2025, 25(18), 5831; https://doi.org/10.3390/s25185831 - 18 Sep 2025
Viewed by 554
Abstract
This paper presents a real-time smart mirror system combining multiple AI modules for multimodal health monitoring. The proposed platform integrates three core components: facial expression analysis, remote photoplethysmography (rPPG), and conversational AI. A key innovation lies in transforming the Moving Average rPPG (MA-rPPG) [...] Read more.
This paper presents a real-time smart mirror system combining multiple AI modules for multimodal health monitoring. The proposed platform integrates three core components: facial expression analysis, remote photoplethysmography (rPPG), and conversational AI. A key innovation lies in transforming the Moving Average rPPG (MA-rPPG) model—originally developed for offline batch processing—into a real-time, continuously streaming setup, enabling seamless heart rate and peripheral oxygen saturation (SpO2) monitoring using standard webcams. The system also incorporates the DeepFace facial analysis library for live emotion, age detection, and a Generative Pre-trained Transformer 4o (GPT-4o)-based mental health chatbot with bilingual (English/Korean) support and voice synthesis. Embedded into a touchscreen mirror with Graphical User Interface (GUI), this solution delivers ambient, low-interruption interaction and real-time user feedback. By unifying these AI modules within an interactive smart mirror, our findings demonstrate the feasibility of integrating multimodal sensing (rPPG, affect detection) and conversational AI into a real-time smart mirror platform. This system is presented as a feasibility-stage prototype to promote real-time health awareness and empathetic feedback. The physiological validation was limited to a single subject, and the user evaluation constituted only a small formative assessment; therefore, results should be interpreted strictly as preliminary feasibility evidence. The system is not intended to provide clinical diagnosis or generalizable accuracy at this stage. Full article
(This article belongs to the Special Issue Sensors and Sensing Technologies for Social Robots)
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