CHIST-ERA Program


Summary

Competition year :

2018-2019

 

Deadline (notice or letter of intent) :

May 15th, 2018, 4 PM

 

Deadline (application) :

May 15th, 2018, 4 PM

 

Amount :

Maximum of $300 000 per year

 

Duration :

Maximum of 3 years, non renewable

 

Announcement of results :

October 2018

 

Program rules that prevail are those of the PDF file

CHIST-ERA is a consortium of funding organisations with programmes supporting Information and Communication Sciences and Technologies (ICST). The CHIST-ERA consortium is itself supported by the European Union's Future & Emerging Technologies scheme (FET).

CHIST-ERA promotes multidisciplinary and transnational ICST research with the potential to lead to significant breakthroughs. The funding organisations jointly support research projects selected in the framework of CHIST-ERA, in order to reinforce European capabilities in selected topics.

Content of the Call


Topic 1


Topic 2


Object recognition and manipulation by robots: Data sharing and experiment reproducibility

Big data and process modelling for smart industry


ORMR


BDSI


Indicative budget:


14.3 M€

Proposals must be submitted by international consortia with research partners in at least 3 of the following countries:

Austria (only topic ORMR), Belgium (Wallonia-Brussels), Bulgaria, Canada (Québec), Czech Republic, Estonia, Finland, France, Greece, Ireland, Italy, Lithuania, Poland, Romania, Spain, Sweden, Slovakia, Switzerland, Turkey, United Kingdom (only topic ORMR)

Proposals are evaluated jointly based on criteria of
relevance to the topic, scientific excellence, implementation, and impact.

Each consortium partner is funded separately by a funding organisation.

Each partner must fulfil the conditions of the funding organisation they are applying to, as described in the annex. Industrial partners are eligible to be funded by some funding organisations.

 

Tentative Timeline


11 January 2018, 17:00 CET


Deadline for pre-proposal submission


Mid-March 2018


Notification of accepted pre-proposals


Mid-May 2018, 17:00 CET


Deadline for full proposal submission


October 2018


Notification of accepted proposals


1 December 2018


First possible start date for accepted projects

 

Research Targeted in the Call

Each year, CHIST-ERA launches a call for research proposals in two new topics of emergent scientific importance. This year's call concerns the following topics:

  1. Object recognition and manipulation by robots: Data sharing and experiment reproducibility (ORMR);
  2. Big data and process modelling for smart industry (BDSI).

In previous years, CHIST-ERA calls have targeted quantum computing, consciousness, knowledge extraction, low-power computing, intelligent user interfaces, smart communication networks, adaptive machines, distributed computing, trustworthy cyber-physical systems, human language understanding, security and privacy in the internet of things, terahertz communication, lifelong learning for intelligent systems and visual analytics.

The CHIST-ERA consortium has created a common funding instrument to support international research groups that engage in long-term research in the area of ICT and ICT-based sciences. Through this instrument, funding organisations support and join the European Union's "Future and Emerging Technologies (FET)" agenda. By coordinating their efforts, they can support more diverse research communities, who are able to tackle the most challenging and novel research topics.

Community-defined topics

A workshop was held in Cracow on 21-23 June 2017 to identify important research challenges within the two selected topics. The workshop brought together ICST researchers from across a range of research communities and countries. The delegates identified a number of research challenges, which have formed the scope of this call. Presentations given at the workshop are available on the CHIST-ERA website (http://conference2017.chistera.eu/). Attendance at the workshop is not a prerequisite for submitting an application to this call. The evaluation criterion "Relevance to the Topic" is assessed only based on the topic descriptions below. The workshop presentations can nevertheless provide background information for preparing a proposal.

Nature of research

Submitted proposals should be of a FET-like nature and contribute to the development of an international and multidisciplinary research. The transformative research done in CHIST-ERA should explore new topics with potential for significant scientific and technical impacts in the long term.

The two topics of this year's call are described below.

1st Topic: Object recognition and manipulation by robots: Data sharing and experiment reproducibility (ORMR)

The ability to recognise and manipulate objects is central to robotics. For example, it might be useful for a robot to recognise a certain object requested by a user, and to determine if and how the object can be safely grasped in order to fetch it. However, despite decades of research, such abilities remain limited in practice. Some of the limiting factors are a paucity of usable, large data sets for training robust models for the tasks under study, a lack of objective evaluation protocols to test these models in a comparable way, and more generally the challenge of reproducing results.

The purpose of this call is to progress the field of robotic perception and manipulation, building solid scientific foundations of experimental reproducibility through transparent sharing of data and methods. This call challenges researchers to propose collaborative projects, which will simultaneously address the three pillars of recognition, manipulation and reproducibility within this domain.

Target Outcomes

Projects should aim to enable the development of robots, which are able to accurately recognise and appropriately manipulate objects in various environments. Projects should lead to quantitative results which can be reproduced by others. Project teams should in particular make publicly available all the data, protocol description and software metrics needed to reproduce experiments. Appropriate efforts and means for doing so should be foreseen. Projects should address real-world challenges, and record and annotate robotic perceptions in order to experiment with different approaches for these challenges. Enough data from various environments and contexts should be used to show the robustness of the experimented approaches.

Key challenges are expected to be:

  • Perceiving or predicting physical properties (shape, orientation, mass, fragility, etc.) of objects or environments;
  • Handling of unknown objects and environments;
  • Developing systems which are capable of operating in ambiguous contexts;
  • Managing the perception-action loop;
  • Interaction and cooperation with humans or other robots;
  • Designing safe, secure, robust and ethically-sound systems;
  • Independent and objective evaluation;
  • Criteria and measures for reproducibility.

Approaches to Maximise Expected Impacts

Projects are strongly encouraged to address the following objectives in order to enhance impact:

  • Grant access to the training data, evaluation data and metrics set up by the projects where possible, in order to help build momentum beyond the project consortia;
  • Support the development of objective benchmarks and evaluation strategies for research in this domain;
  • Cross traditional boundaries between disciplines in order to strengthen the community involved in tackling these new challenges. A broad range of disciplines needed to cover the breadth of this topic should be considered and could include expertise and skills in computer vision, embodied cognition, performance evaluation and robot ethics, among others.
  • Training and dissemination with a view to strengthening European research, knowledge and expertise in the topic areas;
  • Expand understanding and engage with stakeholders on the issues of long-term security, ethical and legal issues associated with the adoption of intelligent and autonomous systems.

2nd Topic: Big data and process modelling for smart industry (BDSI)

Industry is becoming increasingly digitized. Production and operational processes generate growing amounts of heterogeneous data, from simple sensor data to complex 3D video streams. This opens the way for new intelligent, flexible, network-centric production and operational approaches where parts, products and machines are interconnected across equipment, companies and value chains. The goal of these approaches is to enable production and operation at higher yield, higher quality, lower costs, lower environmental footprint and increased flexibility. This evolution is often referred to as the fourth industrial revolution, and it is relevant to most industrial sectors.

The aim of this call is to progress basic research on new information technologies for smart industries. Intelligent context-aware automation systems which are fit for purpose need to be developed. Such systems should be generic enough to be reusable in various settings. Success in this area will strengthen European competitiveness both in science and in industry. This topic is a prime opportunity for science and innovation to benefit by working closely together.

Target Outcomes

Projects should combine big data and process modelling for optimal and accurate operation. The developed models should be reusable across various contexts and application domains. Their performance should be measureable in an objective way.

Key challenges and opportunities are expected to be:

  • Large-scale, complex systems in dynamic environments;
  • Designing conceptual models for autonomous or semi-autonomous decision support;
  • Intelligent fusion of multiple data streams;
  • Integration of heterogeneous, structured and unstructured data;
  • Combining a priori knowledge and models with empirically derived data;
  • Undertaking research in collaboration with industrial partners who can provide representative data;
  • Managing to combine the requirements for privacy, security and intellectual property with the need to develop models openly;
  • Taking advantage of collaboration to collect data from multiple international environments (physical, cultural and regulatory);
  • Implement independent evaluation of systems, data and outputs.

Approaches to Maximise Expected Impacts

Projects are strongly encouraged to address the following objectives in order to enhance impact:

  • Where possible, aim to ensure that data used by the project can be made usable beyond the project, in order to help build momentum beyond the project consortia;
  • Take advantage of international collaboration to make impact on multiple countries and markets;
  • Training and dissemination with a view to strengthening European research, knowledge and expertise in the topic areas;
  • Support the development of objective benchmarks and evaluation strategies for research in this domain;
  • Expand understanding and engage with stakeholders on the issues of long-term security, ethical and legal issues associated with the adoption of intelligent and autonomous systems.

CHIST-ERA Website


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