The aim of OpenDR is to develop a modular, open and non-proprietary tool kit for core robotic functionalities by harnessing deep learning to provide advanced perception and cognition capabilities, meeting in this way the general requirements of robotics applications in the applications areas of Healthcare, Agri-Food and Agile Production. The term toolkit in OpenDR refers to a set of deep learning software functions, packages and utilities used to help roboticists to develop and test a robotic application that incorporates deep learning. OpenDR will provide the means to link the robotics applications to software libraries (deep learning frameworks, e.g., tensorflow) and to link it with the operating environment (ROS). OpenDR focuses on the AI and Cognition core technology in order to provide tools that make robotic systems cognitive, giving them the ability to a) interact with people and environments by developing deep learning methods for human centric and environment active perception and cognition, b) learn and categorise by developing deep learning tools for training and inference in common robotics settings, and c) make decisions and derive knowledge by developing deep learning tools for cognitive robot action and decision making. As a result, the developed OpenDR toolkit will also enable cooperative human-robot interaction as well as the development of cognitive mechatronics where sensing and actuation are closely coupled with cognitive systems thus contributing to another two core technologies beyond AI and Cognition. OpenDR will develop, train, deploy and evaluate deep learning models that improve the technical capabilities of the core technologies beyond the current state of the art. It will enable a greater range of robotics applications that can be demonstrated at TRL 3 and above, thus lowering the technical barriers within the prioritised application areas.

In order to support the expanding demands for processing power from emerging HPC applications, within a pragmatic energy envelope, the future HPC systems will incorporate accelerators. One promising approach, towards this end, is the utilization of FPGAs; the main advantage of those devices is that, since they can be reconfigured at any time so as to implement tailor-made application accelerators, their energy efficiency and/or performance, in most of the cases, is much higher than that of CPUs and GPUs. OPTIMA is an SME-driven project aiming to port and optimize a number of industrial applications as well as a set of open-source libraries, utilized in at least 3 different application domains, to two novel FPGA-populated HPC systems, utilizing several innovative programming environments. It is expected that the applications and the libraries will be executed, in those heterogeneous HPC systems at significantly higher energy-efficiency as described by the Energy Delay Product metric (EDP); in particular, the EDP of the OPTIMA applications and libraries when executed on the targeted FPGA-based HPC systems, is expected to be more than 10x higher than that triggered by CPU-based systems and more than 3x higher than the GPU-based ones. The main outcomes of OPTIMA will be that: a) the participating SMEs will gain a significant advantage since they will be able to execute their applications much more efficiently than the competition, b) it will be further proved that Europe is at the forefront of developing efficient FPGA-populated HPC systems and application/libraries taking advantage of them, c) the open-source libraries as well as the open-source applications developed within OPTIMA will allow third parties to easily target FPGA-based HPC systems for their application developments, d) there will be an open-to-use HPC infrastructure supported by a specially formed sustainability body.