IMOCO4.E targets to provide vertically distributed edge-to-cloud intelligence for machines, robots and other human in-the-loop cyber-physical systems having actively controlled moving elements. They face ever-growing requirements on long-term energy efficiency, size, motion speed, precision, adaptability, self-diagnostic, secure connectivity or new human-cognitive features.


IMOCO4.E strives to perceive and understand complex machines and robots. The two main pillars of the project are digital twins and AI principles (machine/deep learning). The subsequent mission is to bring adequate edge intelligence into the Instrumentation and Control Layers, to analyse and process machine data at the appropriate levels of the feedback control loops and to synchronise the digital twins with either simulated or real-time physical world. At all levels, AI techniques are employable.


Summing up, IMOCO4.E strives to deliver a reference platform consisting of AI and digital twin toolchains and a set of mating building blocks for resilient manufacturing applications. The optimal energy efficient performance and easy (re)configurability, traceability and cyber-security are crucial. The IMOCO4.E reference platform benefits will be directly verified in applications for semicon, packaging, industrial robotics and healthcare. Additionally, the project demonstrates the results in other generic  motion-control-centred domains. The project outputs will affect the entire value chain of the production automation and application markets.


IMOCO4.E will significantly strengthen European industrial competitiveness through the IMOCO4.E reference platform, which will be directly verified in applications for semiconductor, packaging, industrial robotics and healthcare. Additionally, the project demonstrates the results in other generic "motion-control-centred" domains. It will bridge the gap between the latest research results and industrial practice to improve performance as measured by a whole variety of parameters including response time, reliability, predictive maintenance, control accuracy and error. Furthermore, a reduction of 40% in the development of digital twins of a machine tool can be expected by the application of the model-based approach. The envisioned platform will be particularly suitable for applications where the dynamics and precision of the controlled motion are crucial and not straightforward. Easy re-configurability and/or reuse is of benefit for being flexible during the development.


IMOCO4.E mainly relates to the following major challenges from the ECSEL Multi Annual Strategic Plan (ECSEL MASP 2020):

  • Managing critical, autonomous, cooperating, evolvable systems (Chapter 6)
  • Increasing compactness and capabilities by functional and physical systems integration (Chapter 6)
  • Safety, security and privacy by design (Chapter 8)
  • Increasing performance at acceptable costs (Chapter 9)
  • Making computing systems more integrated with the real world (Chapter 9)
  • Making "intelligent" machines (Chapter 9)
  • AI-enabled cognitive, resilient, adaptable manufacturing (Chapter 4)
  • Moving healthcare from hospitals into our homes and daily life requiring preventive and patient centric care (Chapter 2)

Scientific & technical development objectives

  • To develop advanced model-based and knowledge-based methods for building digital twins for design, optimization, customization, virtual commissioning and predictive maintenance of machines and robots, using existing and novel data sets
  • To develop a smart Instrumentation Layer gathering and processing visual and/or sensor information from supplementary instrumentation installed on the moving parts of the controlled system (i.e., at the edge) to enhance the achievable performance and energy efficiency during whole system lifecycle
  • To develop modular unified, Hardware and Software motion control building blocks.
  • Ensure secure interoperability with State-of-the-Art cloud platform, i.e. System Behaviour Layer – Layer 3 and develop specific condition monitoring building blocks providing relevant data for machine digital twins and system behaviour layer, further used either for machine predictive maintenance or re-design, virtual design and optimization; contribute to EU Open Datasets.

Work packages

Leader: Sioux Technologies
Duration: M1-M36
The main objective of this work package is to execute all the project management procedures. Specifically, the management structure and managing procedures that the project will adopt and endorse have the following objectives:
  • To manage and control the project's activities, task schedules and resources within the consortium
  • To ensure the truly integration between work package deliverables and tasks
  • To check the consistency between the overall project goals, ST, SO, SI objectives, developments and achievements f all concerned parties
  • To develop and manage the quality aspects of the project
  • To report and maintain liaisons with the EC
  • To assure networking with other EU financed projects

Leader: ITEC B.V.
Duration: M1-M14
WP2 specifies the requirements for setting up a structured framework and plan of actions for development of the technical work packages.

Leader: Elektronikas un Datorzinatnu Instituts
Duration: M4-M30
Perception and instrumentation layer address all the necessary technologies to sense/perceive, process (locally) and manipulate the physical properties of the controlled system. This work package deals with the design of low-power/ self-powered sensors (also wireless sensors), new SoC, FPGA and multi-many core platforms for AI and smart data processing as well as AI based perception systems and modules to work in smart mechatronic and robotic applications, and high-speed servo drives, variable speed drives. Despite different sensors, platforms, systems and modules IMOCO4.E strives for a unified (where possible standardized) interface for easier integration. 

Leader: Tekniker
Duration: M4-M30
WP4 specifies development of high-precision motion control algorithms intended for general purpose industrial actuator drives.

Leader: Brno University of Technology
Duration: M4-M30
The aim of WP5 is to push forward the digital twin concept in industrial applications. It targets twinning for commissioning (part of the system design domain), for assembly, for training (both are part of the production domain), and for maintenance (for service instructions). It also deals with secure communication interfaces and data management which are needed to support the storage of increasing amounts of data being generated by digital twins, by expanding sensory systems and processed by data-hungry NN learning algorithms.

Leader: University of West Bohemia
Duration: M9-M36
The purpose of this work package is to create a homogeneous system deliverable, comprising hardware, software processes and procedures, that embody the IMOCO4.E concept and ensure that it is optimally delivered. More specifically, the results of the research and development carried out in work packages 3, 4 and 5 should be integrated into a set of universally applicable building blocks. WP6 aims at integration, evaluation and validation of all IMOCO4.E technical developments including pilots set up in WP7. While the feasibility of the project concepts and components is practically proven in WP7, its effectiveness will be measured and analysed in WP6. Following an evolutionary development approach, the experiences and insights gained here will be communicated to WP3, WP4 and WP5 in order to support the future applicability of the IMOCO4.E results in real-life manufacturing scenarios.

Leader: Philips Consumer Lifestyle
Duration: M6-M36
The main objectives of WP7 are the demonstration and validation of IMOCO4.E developments in different mechatronic domains at machine level (SO1) and in different production environments (clean/harsh) at shop floor level (SO2).

Leader: ITML
Duration: M1-M36
WP8 specifies dissemination, exploitation and communication activities of IMOCO4.E.