IEEE RO-MAN'17: Workshop on ARtificial Perception, MAchine Learning and DAtasets for Human-Robot Interaction (ARMADA'17)

Abstract
Robotics is increasingly moving towards the research and development of  technologies that allow the introduction of robots in our daily life. The optimal robot assistant should share a human environment and be able to cope with human presence and interact in a very friendly way. To create such applications a number of problems need to be solved, including artificial perception systems and reasoning techniques to interpret human interactions to endow robots that can successfully act as assistants. Examples where intelligent robots are usually employed are: caretakers for the elderly and for disabled people, service robots, assistants in surgery and patient rehabilitation, and educational toys. The expectation of having intelligent robots lead us to think that in order for this to happen, many topics must be considered, including advanced perception for autonomous systems. This challenge is particularly relevant to a new generation of robots, which must interact with people, and operate in human environments, dealing with uncertainties, and surrounded by many types of static and dynamic objects.


Aim
The aim of this workshop is to bring together researchers to discuss current and future challenges of advanced/intelligent sensor-based perception systems for human-robot interaction and share their experience in this research topic, in particular:
- Machine learning and intelligent algorithms for perception and recognition systems within the context of HRI.
- Multimodal sensor datasets (Mono and Stereo Vision, RGB-D, IMU, LRF) and evaluation metrics.

The ARMADA’17 Workshopto be held in conjunction with IEEE RO-MAN 2017, welcomes contributions reporting on original research, work under development and experiments of different fields related to machine learning and perception systems for human-robot interaction scenarios.


Topics of interest 
1. Artificial intelligence and machine learning algorithms for HRI
2. ML and intelligent algorithms applied to perception systems
3. ML and perception for assistive robotics; robotic walker; robotic head
4. Context-based perception for HRI
5. Environment perception and/or scene understanding
6. Cooperative perception
7. Multimodal sensor datasets (Mono, Stereo and Thermal cameras, RGB-D, MoCap, IMU, LRF, etc.)
8. Benchmarking HRI in robotic applications
9. HRI metrics (including teams)
10. Activity and action recognition
11. Social activity recognition
12. Affective computing
13. Human behaviour analysis


Speakers
- Prof Estela Guerreiro Silva Bicho Erlhagen (University of Minho)
- Prof Jorge Dias (University of Coimbra | Khalifa University)
- Prof Adriana Tapus (ENSTA-ParisTechl)

Special Issue (ARMADA'17)
Selected accepted papers will be invited to submit extended versions to:
Paladyn - Journal of Behavioral Robotics

https://www.degruyter.com/page/1531


Organizers
Affiliation: School of Engineering and Applied Science, Aston University,
Birmingham, UK.
Phone: +44 1212 044 868
Email address: d.faria@aston.ac.uk

Affiliation: Department of Electrical and Computer Engineering, University of Coimbra
Address: ISR-UC, University of Coimbra, Polo II, 3030-290 Coimbra Portugal
Phone: +351 239 796 214
Email address: cpremebida@isr.uc.pt

Collaboration



WS Technical Program Committee
Professor Jorge Dias, University of Coimbra (PT) / Khalifa University (UAE)
Professor Fulvio Mastrogiovanni, University of Genoa (IT)
Professor Estela Bicho, University of Minho (PT)
Dr Barbara Bruno, University of Genoa (IT)
Dr Luis J Manso, University of Extremadura (ES)
Dr Ricardo Martins, IBILI-CN, University of Coimbra (PT)
Dr Cristiano Premebida, ISR-UC, University of Coimbra (PT)
Dr Diego R. Faria, Aston University (UK)