Novel paradigms and approaches, towards AI-driven autonomous robots (AI, data and robotics partnership) (RIA)

The currently low level of autonomy achieved by most robotics systems is a major obstacle to the wide-scale deployment of robots with advanced capabilities in many real-world applications. Most robots still require an important level of human supervision. However, in many potentially valuable applications robots need to work with greater levels of autonomy to create effective end user added value.

Future robotic systems will be required to autonomously adapt and alter their behaviours to respond to changes in the working environment and adjust to changes in task requirements without direct human supervision.

Achieving next step autonomy in robotics will require greater integration of AI technologies into the physical functioning of robots. This in turn requires AI to operate in real time at pace with the physical motion of the robot. Interpreting the working environment, interacting with complex objects or people and making and updating decision making, all in real time, requires a significant advance from the current state of the art. This will require novel architectures both in software and hardware and will require AI algorithms compatible with physical, real time, robot operation. In terms of R&I advancement a paradigm shift is needed to remove silos between disciplines in order to weld together expertise and create a conceptual shift to reach the goals of next step autonomy for robotics.

The primary outcome will be that important applications for robots become possible as a result of achieving next step autonomy in specific use cases and sectors.

Achieving this goal will require improvements in perception, awareness of the operating environment, the ability to anticipate and an improved understanding of the consequences of particular sequences of action on the working environment.

Proposals will need to address safety and security aspects at all levels, as well as consider the handling of data collection (respecting relevant regulation such as the GDPR and the revised Machinery Directive).

Proposals should address the interdependence between safety, security and system performance with respect to the chosen application or use case.

Proposals should address several of the following aspects of autonomy:

• Long-term, and where appropriate lifelong, autonomy of behaviour and energy (including frugality in terms of energy, lower environmental footprint, using new materials, designed to be recycled or easily repaired etc.)
• The autonomous adaptation of behaviours in dynamic environments.
• The development of robust and safe autonomy, including the development of risk averse systems or systems operating with low levels of communication or periods of communication denial.
• The use of high-level sources of information such as semantic information or externally held knowledge of the working environment, to improve autonomy.
• Mechanisms for advanced human interaction with systems capable of long-term autonomy.
• The impact of physical self-reconfiguration on autonomy
• The development of collective autonomy using multiple collaborative robots

Multidisciplinary research activities should address all of the following:

• Proposals should involve appropriate expertise in all relevant disciplines. Social Sciences and Humanities (SSH) is particularly relevant in addressing aspects related to human-robot interaction, sensible task distribution between humans and robots, agency, control, trust and handling of data collection, to achieve usability, trustworthiness, safety and adoption of the developed solutions.
• It is essential that scientific and technological results should bear reproducible and re-usable in order to contribute to the advancement of the targeted research area.
• S&T progress should be demonstrated through use-cases with major and broad socio-economic impact.
• End-users should be involved, as scenario providers, to set the requirements, success criteria and context, for the targeted sectors and/or use-cases that inform the technological challenges to be addressed in the projects.
• Projects should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives.
• Contribute to making AI and robotics solutions meet the requirements of Trustworthy AI, based on the respect of the ethical principles, the fundamental rights including critical aspects such as robustness, safety, reliability, in line with the European Approach to AI. Ethics principles needs to be adopted from early stages of development and design.

All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring, as well as illustrative application use-cases demonstrating well defined potential added value to end-users), and share communicable results with the European R&D community, through the AI-on-demand platform or Digital Industrial Platform for Robotics, public community resources, to maximise re-use of results, either by developers, or for uptake, and optimise efficiency of funding; enhancing the European AI, Data and Robotics ecosystem through the sharing of results and best practice.

This topic implements the co-programmed European Partnership on AI, data and robotics.