2nd Call for Papers: SUBMISSIONS OPEN!

AVHRC 2020 – Active Vision and perception in Human(-Robot) Collaboration Workshop
@RO-MAN 2020 – THE 29TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION
NAPLES, ITALY, FROM AUGUST 31 TO SEPTEMBER 4, 2020.

Key Dates
=========

Submission opening: May 1, 2020
Submission deadline: June 25, 2020
Notification: July  15, 2020
Camera ready July 30, 2020
Workshop: August 31, 2020

**Workshop website: ***
https://www.essex.ac.uk/departments/computer-science-and-electronic-engineering/events/avhrc-2020

**Submission website: ***
https://easychair.org/conferences/?conf=avhrc2020

Publication
============

All accepted papers will be published on the workshop website.
Selected papers will be published with a discounted fee in a dedicated topic of Frontiers in Neurorobotics: https://www.frontiersin.org/research-topics/13958/active-vision-and-perception-in-human-robot-collaboration

A best paper award will be announced, offering a full publication fee waiver.

Submission Guidelines
=====================

Two types of submissions are invited to the workshop: long papers (6 to 8 pages + n references pages) and short papers (2-4 pages + n references pages). In both cases there is no page limit for the bibliography/references (n pages) section.       

All submissions should be formatted according to the standard IEEE RAS Formatting Instructions and Templates avialble at http://ras.papercept.net/conferences/support/tex.php. Authors are required to submit their papers electronically in PDF format.

Submission link: https://easychair.org/conferences/?conf=avhrc2020

At least one author of each accepted paper must register for the workshop. 
For any questions regarding paper submission, please email us: dimitri.ognibene@gmail.com

Presentation
==============

Papers will be presented in short talks and/or poster spotlights.
The organisers would like to reassure authors that, independently of any potential restriction due to the COVID-19 situation, it will be possible to present all accepted papers and to attend the keynotes, either in person or remotely, following the same rules and the same procedure of the main conference. At what is a difficult time for many people, we look forward to sharing our work with the community despite any restrictions and we invite interested colleagues to join us. More information can be found here: http://ro-man2020.unina.it/announcements.php

Topics
========

•       Cognitive Social Robotics.
•       Active perception for intention and action prediction
•       Activity and action perception in ecological conditions
•       Bioinspired and neuromorphic vision for activity recognition
•       Active perception for social interaction
•       Active perception for social navigation
•       Brain-Inspired solutions for active social perception
•       Human-robot collaboration in unstructured environments
•       Human-robot collaboration in presence of sensory limits
•       Joint Human-Robot search and exploration
•       Testing setup for social perception in real or virtual environments
•       Setup for transferring active perception skills from humans to robots
•       Machine learning methods for active social perception
•       Benchmarking and quantitative evaluation with human subject experiments
•       Gaze-based Factors for Intuitive Human-Robot Collaboration
•       Active perception modelling for social interaction and collaboration
•       Head-mounted eye tracking and gaze estimation during social interaction
•       Estimation and guidance of partner situation awareness and attentional state in human-robot collaboration
•       Multimodal active social perception
•       Adaptive embodied social perception
•       First Person (Egocentric) Vision for Actions and Object Recognition and Anticipation
•       Egocentric vision in social interaction;
•       Explicit and implicit sensorimotor communication;
•       Social attention;
•       Natural human-robot (machine) interaction;
•       Joint attention;
•       Multimodal social attention;
•       Attentive activity recognition;
•       Belief and mental state attribution in robots

Invited Speakers
================

        • Giulio Sandini, Italian Institute of Technology, Italy
        • Fiora Pirri, Università di Roma “La Sapienza”, Italy
        • Tom Foulsham, University of Essex, UK
        • Angelo Cangelosi, University of Manchester, UK
        • David Rudrauf, University of Geneve, Switzerland
        • Giuseppe Boccignone, Università di Milano, Italy

Background
=============

Humans naturally interact and collaborate in unstructured social environments that produce an overwhelming amount of information and may yet hide behaviourally relevant variables. Finding the underlying design principles that allow humans to adaptively find and select relevant information is important for Robotics but also other fields, such as Computational Neuroscience, Interaction Design, and Computer Vison.

Current solutions cover specific tasks, e.g. autonomous cars, and usually employ over-redundant, expensive, and computationally demanding sensory systems that attempt to cover the wide set of sensing conditions which the systems may have to deal with. A promising alternative is to take inspiration from the brain. Adaptive control of sensors and the perception process is a key solution found by nature to cope with computational and sensory demands, as shown by the foveal anatomy of the eye and its high mobility.

Alongside this application of “active” vision, collaborative robotics has recently progressed to human-robot interaction in real manufacturing.

Partners’ gaze behaviours are a crucial source of information that humans exploit for collaboration and coordination. Thus measuring and modelling task-specific gaze behaviours seems to be essential for smooth human-robot interaction. Indeed, anticipatory control for human-in-the-loop architectures, which can enable robots to proactively collaborate with humans, could gain much from parsing the gaze and actions patterns of the human partners.

We are interested in manuscripts that present novel, brain inspired computational and robotic models, theories and experimental results as well as reviews relevant to these topics. Submissions should further our understanding of how humans actively control their perception during social interaction, in which conditions they fail, and how these insights may enable natural interaction between humans and embodied artificial systems in non-trivial conditions.

Organizers
==================

Main organiser
        Dimitri Ognibene, University of Essex, UK & University of Milano-Bicocca, Italy

Communication Organisers

        Francesco Rea, Instituto Italiano di Tecnologia, Italy
        Francesca Bianco,University of Essex, UK
        Vito Trianni, ISTC-CNR, Italy
        Ayse Kucukyilmaz, University of Nottingham, UK
        Lucas Paletta, JOANNEUM RESEARCH, Austria

Review Organisers

        Angela Faragasso,  The University of Tokyo, Japan
        Manuela Chessa, University of Genova
        Fabio Solari, University of Genova
        David Rudrauf,  University of Geneve, Switzerland
        Yan Wu,  Robotics Department, Institute for Infocomm Research, A*STAR, Singapore

Publication Organisers

        Fiora Pirri, Sapienza – University of Rome, Italy
        Letizia Marchegiani, Aalborg University, Denmark
        Tom Foulsham, University of Essex, UK
        Giovanni Maria Farinella, University of Catania, Italy

========================================================================
Vito Trianni, Ph.D.                                     vito.trianni@(no_spam)istc.cnr.it
ISTC-CNR                                                http://www.istc.cnr.it/people/vito-trianni
Via San Martino della Battaglia 44              Tel: +39 06 44595277
00185 Roma                                              Fax: +39 06 44595243
Italy
========================================================================

Note that ICAS 2020 scheduled earlier in the year has been moved to September 27 – October 01, 2020 in Lisbon, Portugal. As such, we have additional time to reopen submissions to the conference.

In order to accommodate a large number of situations, we are offering the option for either physical presence or virtual participation. We would be delighted if all authors manage to attend, but are aware that special circumstances are best handled by having flexible options.

The submission deadline is May 18.

Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to:

– ICAS 2020, The Sixteenth International Conference on Autonomic and Autonomous Systems

Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org

=================

============== ICAS 2020 | Call for Papers ===============

CALL FOR PAPERS, TUTORIALS, PANELS

ICAS 2020, The Sixteenth International Conference on Autonomic and Autonomous Systems

General page: http://www.iaria.org/conferences2020/ICAS20.html

Submission page: http://www.iaria.org/conferences2020/SubmitICAS20.html

Event schedule: September 27 – October 01, 2020 – Lisbon, Portugal

Contributions:

– regular papers [in the proceedings, digital library]

– short papers (work in progress) [in the proceedings, digital library]

– ideas: two pages [in the proceedings, digital library]

– extended abstracts: two pages [in the proceedings, digital library]

– posters: two pages [in the proceedings, digital library]

– posters:  slide only [slide-deck posted at www.iaria.org]

– presentations: slide only [slide-deck posted at www.iaria.org]

– demos: two pages [posted at www.iaria.org]

Submission deadline: May 18, 2020

Sponsored by IARIA, www.iaria.org

Extended versions of selected papers will be published in IARIA Journals:  http://www.iariajournals.org

Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html

Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org

The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.

All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.

Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html

ICAS 2020 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2020/CfPICAS20.html

============================================================

SELFTRENDS: Toward brain-like autonomic and autonomous systems

Adaptive robust resource allocation; Optimal self-organized collective actions; Collective adaptation; Active learning;  Opportunistic collaborative interactive learning; Adaption fairness; Social and biometric data-aware adaptation; Brain connectivity models;  Using unbalanced Datasets;  Quantum-inspired optimization; Automated (industrial) assembly environments; Deep neural networks; Multimodal knowledge of the brain; Self-organization in M2M infrastructures; Self-organizing socio-technical systems; Context-aware data self-adaptation; Multi-level loop encapsulation in smart systems; Uncertainty in self-adaptive systems; Adaptive Software defined systems (SDS) scalability; Adaptability in multi-tenant Clouds; Self-aware model-driven systems; Proactive self-adaptation; Self-adaptive urban traffic; Adaptive power profiling; Run-time for self-adaptive systems; Distributed adaptive systems; Self-improving system integration; Self-improving activity recognition systems; Feedback computing; Optimal feedback control; Dynamic adaptive applications; Self-managing Clouds;  Decentralized autonomic behavior; Market-adaptive trust;  Semantics of self-behavior;  Self-organizing patterns; Stability propagation in self-organizing systems; Inconsistency in self-deciding systems; Reasoning problems tractability; Decidability in self-organizing systems

ROBOTRENDS: Robot-related trends

Autonomous aquatic agents; Aerial autonomous robots; Drones control and management; Knowledge-based robot motions; Autonomous mobile robot interaction; Humanoid robots; Intelligent robots; Self-reconfigurable mobile robots; Humanoid imitative learning; Robots in unknown environments; Human centric robots; Adjustable robust optimizations; Moral autonomous agents and human evolution; Cognitive robotics; Robot partnership; Affective communication robots; Human-centric robotics; Visually-impaired and robots; Evolutionary swarm robotics; Robots and human advices; Universal robot hands

MACHINE LEARNING: Advanced topics in Deep/Machine learning

Distributed and parallel learning algorithms; Image and video coding; Deep learning and Internet of Things; Deep learning and Big data; Data preparation, feature selection, and feature extraction; Error resilient transmission of multimedia data; 3D video coding and analysis; Depth map applications; Machine learning programming models and abstractions; Programming languages for machine learning; Visualization of data, models, and predictions; Hardware-efficient machine learning methods; Model training, inference, and serving; Trust and security for machine learning applications; Testing, debugging, and monitoring of machine learning  applications; Autonomous and robotics systems; Machine learning for systems.

SYSAT: Advances in system automation

Methods, techniques ant tools for automation features; Methodologies for automating of design systems; Industrial automation for production chains; Nonlinear optimization and automation control; Nonlinearities and system stabilization; Automation in safety systems; Structured uncertainty; Open and closed automation loops; Test systems automation; Theory on systems robustness; Fault-tolerant systems

UNMANNED: Driver-less cars and unmanned vehicles

Self-driving cars; Drones; Terrestrial unmanned vehicles; Unmanned aerial vehicles; Underwater unmanned vehicles; Unmanned sea surface vehicles; Collision control; Traffic surveillance challenges; Path planning and estimation; Communication between unmanned vehicles; Integration of unmanned aerial vehicles in civil airspace; Unmanned vehicular clusters; Designing unmanned vehicular-based systems; Safety of unmanned vehicles; Commercial and surveillance applications; Emergency applications; Legal aspects of unmanned vehicular systems; Testbeds and pilot experiments

AUTSY: Theory and Practice of Autonomous Systems

Design, implementation and deployment of autonomous systems; Frameworks and architectures for component and system autonomy; Design methodologies for autonomous systems; Composing autonomous systems; Formalisms and languages for autonomous systems; Logics and paradigms for autonomous systems; Ambient and real-time paradigms for autonomous systems; Delegation and trust in autonomous systems; Centralized and distributed autonomous systems; Collocation and interaction between autonomous and non-autonomous systems; Dependability in autonomous systems; Survivability and recovery in autonomous systems; Monitoring and control in autonomous systems; Performance and security in autonomous systems; Management of autonomous systems; Testing autonomous systems; Maintainability of autonomous systems

AWARE: Design and Deployment of Context-awareness Networks, Services and Applications

Context-aware fundamental concepts, mechanisms, and applications; Modeling context-aware systems; Specification and implementation of awareness behavioral contexts; Development and deployment of large-scale context-aware systems and subsystems; User awareness requirements and design techniques for interfaces and systems; Methodologies, metrics, tools, and experiments for specifying context-aware systems; Tools evaluations, Experiment evaluations

AUTONOMIC: Autonomic Computing: Design and Management of Self-behavioral Networks and Services

Theory, architectures, frameworks and practice of self-adaptive management mechanisms; Modeling and techniques for specifying self-ilities; Self-stabilization and dynamic stability criteria and mechanisms; Tools, languages and platforms for designing self-driven systems; Autonomic computing and GRID networking; Autonomic computing and proactive computing for autonomous systems; Practices, criteria and methods to implement, test, and evaluate industrial autonomic systems; Experiences with autonomic computing systems

CLOUD: Cloud computing and Virtualization

Hardware-as-a-service; Software-as-a-service [SaaS applicaitions]; Platform-as-service; On-demand computing models; Cloud Computing programming and application development; Scalability, discovery of services and data in Cloud computing infrastructures; Privacy, security, ownership and reliability issues; Performance and QoS; Dynamic resource provisioning; Power-efficiency and Cloud computing; Load balancing; Application streaming; Cloud SLAs, business models and pricing policies; Custom platforms; Large-scale compute infrastructures; Managing applications in the clouds; Data centers; Process in the clouds; Content and service distribution in Cloud computing infrastructures; Multiple applications can run on one computer (virtualization a la VMWare); Grid computing (multiple computers can be used to run one application); Virtualization platforms; Open virtualization format; Cloud-computing vendor governance and regulatory compliance

MCMAC: Monitoring, Control, and Management of Autonomous Self-aware and Context-aware Systems

Agent-based autonomous systems; Policy-driven self-awareness mechanisms and their applicability in autonomic systems; Autonomy in GRID networking and utility computing; Studies on autonomous industrial applications, services, and their developing environment; Prototypes, experimental systems, tools for autonomous systems, GRID middleware

CASES: Automation in specialized mobile environments

Theory, frameworks, mechanisms and case studies for satellite systems; Spatial/temporal constraints in satellites systems; Trajectory corrections, speed, and path accuracy in satellite systems; Mechanisms and case studies for nomadic code systems; Platforms for mobile agents and active mobile code; Performance in nomadic code systems; Case studies systems for mobile robot systems; Guidance in an a priori unknown environment; Coaching/learning techniques; Pose maintenance, and mapping; Sensing for autonomous vehicles; Planning for autonomous vehicles; Mobile networks, Ad hoc networks and self-reconfigurable networks

ALCOC: Algorithms and theory for control and computation

Control theory and specific characteristics; Types of computation theories; Tools for computation and control; Algorithms and data structures; Special algorithmic techniques; Algorithmic applications; Domain case studies; Technologies case studies for computation and control; Application-aware networking

MODEL: Modeling, virtualization, any-on-demand, MDA, SOA

Modeling techniques, tools, methodologies, languages; Model-driven architectures (MDA); Service-oriented architectures (SOA); Utility computing frameworks and fundamentals; Enabled applications through virtualization; Small-scale virtualization methodologies and techniques; Resource containers, physical resource multiplexing, and segmentation; Large-scale virtualization methodologies and techniques; Management of virtualized systems; Platforms, tools, environments, and case studies; Making virtualization real; On-demand utilities; Adaptive enterprise; Managing utility-based systems; Development environments, tools, prototypes

SELF: Self-adaptability and self-management of context-aware systems

Novel approaches to modeling and representing context adaptability, self-adaptability, and self-manageability; Models of computation for self-management context-aware systems; Use of MDA/MDD (Model Driven Architecture / Model Driven Development) for context-aware systems; Design methods for self-adaptable context-aware systems; Applications of advanced modeling languages to context self-adaptability; Methods for managing adding context to existing systems and context-conflict free systems; Architectures and middleware models for self-adaptable context-aware systems; Models of different adaptation and self-adaptation mechanisms (component-based adaptation approach, aspect oriented approach, etc.); System stability in the presence of context inconsistency; Learning and self-adaptability of context-aware systems; Business considerations and organizational modeling of self-adaptable context-aware systems; Performance evaluation of self-adaptable context-aware systems; Scalability of self-adaptable context-aware systems 

KUI: Knowledge-based user interface

Evolving intelligent user interface for WWW; User interface design in autonomic systems; Adaptive interfaces in a knowledge-based design; Knowledge-based support for the user interface design process; Built-in knowledge in adaptive user interfaces; Requirements for interface knowledge representation; Levels for knowledge-based user interface; User interface knowledge on the dynamic behavior; Support techniques for knowledge-based user interfaces; Intelligent user interface for real-time systems; Planning-based control of interface animation; Model-based user interface design; Knowledge-based user interface migration; Automated user interface requirements discovery for scientific computing; Knowledge-based user interface management systems; 3D User interface design; Task-oriented knowledge user interfaces; User-interfaces in a domestic environment; Centralised control in the home; User-interfaces for the elderly or disabled; User-interfaces for the visually, aurally, or mobility impaired; Interfacing with ambient intelligence systems; Assisted living interfaces; Interfaces for security/alarm systems

AMMO: Adaptive management and mobility

QoE and adaptation in mobile environments; Content marking and management (i.e. MPEG21); Adaptive coding (H.265, FEC schemes, etc.. ); Admission control resource allocation algorithms; Monitoring and feedback systems; Link adaptation mechanisms; Cross layer approaches; Adaptation protocols (with IMS and NGNs scenarios); QoE vs NQoS mapping systems; Congestion control mechanisms; Fairness issues (fair sharing, bandwidth allocation…); Optimization/management mechanisms (MOO, fuzzy logic, machine learning, etc.)