Periodic Reporting for period 2 - MASTERLY (Nimble Artificial Intelligence driven robotic solutions for efficient and self-determined handling and assembly operations)
Periodo di rendicontazione: 2024-07-01 al 2025-06-30
Over the last years, production has been shifted from mass production to customization. The conventional production lines, traditionally focused on one product variant or one family of products, do show their limitations to cope with the new needs. Moreover, unprecedented worldwide events, such as the recent pandemic crisis, indicated even more the need for flexible production systems that can rapidly switch production to a totally different one. It was revealed though that current production paradigms present drawbacks that limit the flexibility in production switch.
MASTERLY project pioneers technological advancements that facilitate a seamless transition from mass production to customization. It aims to develop flexible robotic solutions comprised of modular grippers and cutting-edge technologies. These include mobile and stationary industrial robots with varying payloads, collaborative robots, and smart cranes, all enhanced with AI-driven control and perception capabilities. This allows them to autonomously handle a wide variety of parts, differing in size, shape, and material, and ensures usability across all workforce genders.
In order to meet this challenge, MASTERLY consortium aims to work based on the following five objectives:
• Innovative, efficient and low consumption systems for storage, retrieval, conveying and pick-and-place using a multi-disciplinary approach combining technologies
• Robust handling devices and systems, with integrated –AI driven– advanced control
• User-friendly interfaces for robot/machine control and programming
• Interoperable S/W and H/W interfaces
• Industrial Pilot Cases for work piece handling in full production line
The proposed technologies will be tested for flexibility, efficiency and user acceptance in three use cases from different productions sectors, aiming to demonstrate production line and cross sector applicability, scalability and adaptability:
• Elevators manufacturing, focusing on the assembly of electrical cabinets of lifts,
• Sportswear, focusing on warehouse logistics and packaging and
• Aeronautics production, focusing on production of large composite panels of aircraft wings.
MASTERLY project pioneers technological advancements that facilitate a seamless transition from mass production to customization. It aims to develop flexible robotic solutions comprised of modular grippers and cutting-edge technologies. These include mobile and stationary industrial robots with varying payloads, collaborative robots, and smart cranes, all enhanced with AI-driven control and perception capabilities. This allows them to autonomously handle a wide variety of parts, differing in size, shape, and material, and ensures usability across all workforce genders.
In order to meet this challenge, MASTERLY consortium aims to work based on the following five objectives:
• Innovative, efficient and low consumption systems for storage, retrieval, conveying and pick-and-place using a multi-disciplinary approach combining technologies
• Robust handling devices and systems, with integrated –AI driven– advanced control
• User-friendly interfaces for robot/machine control and programming
• Interoperable S/W and H/W interfaces
• Industrial Pilot Cases for work piece handling in full production line
The proposed technologies will be tested for flexibility, efficiency and user acceptance in three use cases from different productions sectors, aiming to demonstrate production line and cross sector applicability, scalability and adaptability:
• Elevators manufacturing, focusing on the assembly of electrical cabinets of lifts,
• Sportswear, focusing on warehouse logistics and packaging and
• Aeronautics production, focusing on production of large composite panels of aircraft wings.
During the 2nd period of the project, the technology prototypes of MASTERLY modules have been integrated in the lab scale pre-pilot demonstrators of TF-CC, STAM and TEKNIKER.
• The elevators manufacturing pre-industrial testbed of TF-CC has been used for the preliminary integration and validation of the following MASTERLY technologies’ final prototypes as follows:
o COMAU autonomous mobile manipulator equipped with the Cobot5 flexible robotic arm for transportation tasks’ execution.
o Dexterous gripper for rigid parts towards electrical parts’ removal from the box container and assembly on the corresponding rails.
o Impedance Control for electrical component assembly based on force sensor data.
o Pose and grasping point estimation for assembly parts’ detection.
o Digital twin framework for mobile manipulators.
o Dynamic task and actions planning tool for assembly tasks allocation to available resources of the KLEEMANN pilot.
o AR application enabling Human-Robot Interaction in the KLEEMANN pilot for operator support and robot control.
• The following MASTERLY technologies’ final prototypes have been tested inside the STAM pre-pilot testbed for the DECATHLON pilot:
o COMAU flexible robotic arm Racer5 cobot for required manipulation tasks’ execution.
o Modular gripper for flexible materials’ handling.
o Vision-based objects' geometry estimation either based on CAD models of CAD-less approach for required part’s detection inside the robotic cell
o Digital twin at cell and process level.
o Tablet application towards operator’s interaction with the WorkFlow Controller and the production system.
o WorkFlow controller responsible for the orchestration and monitoring of assembly schedule execution by the available resources.
• The following MASTERLY technologies final prototypes have been tested inside the TEKNIKER pre-pilot testbed in terms of the aeronautic pilot case of the project:
o Smart crane for autonomous transportation.
o Vision-based objects' geometry estimation to precisely detect the location of the part inside the testbed’ layout.
o Digital twin at cell and process level.
o AR operator support application based on AR glasses enabling human operators interaction with the WorkFlow Controller.
o WorkFlow controller responsible for the orchestration and monitoring of assembly schedule execution by the available resources.
Through these integration activities, valuable feedback has been collected towards the fine-tuning of MASTERLY modules and the delivery of MASTERLY final prototypes at the industrial demonstrators during the 3rd period of the project.
• The elevators manufacturing pre-industrial testbed of TF-CC has been used for the preliminary integration and validation of the following MASTERLY technologies’ final prototypes as follows:
o COMAU autonomous mobile manipulator equipped with the Cobot5 flexible robotic arm for transportation tasks’ execution.
o Dexterous gripper for rigid parts towards electrical parts’ removal from the box container and assembly on the corresponding rails.
o Impedance Control for electrical component assembly based on force sensor data.
o Pose and grasping point estimation for assembly parts’ detection.
o Digital twin framework for mobile manipulators.
o Dynamic task and actions planning tool for assembly tasks allocation to available resources of the KLEEMANN pilot.
o AR application enabling Human-Robot Interaction in the KLEEMANN pilot for operator support and robot control.
• The following MASTERLY technologies’ final prototypes have been tested inside the STAM pre-pilot testbed for the DECATHLON pilot:
o COMAU flexible robotic arm Racer5 cobot for required manipulation tasks’ execution.
o Modular gripper for flexible materials’ handling.
o Vision-based objects' geometry estimation either based on CAD models of CAD-less approach for required part’s detection inside the robotic cell
o Digital twin at cell and process level.
o Tablet application towards operator’s interaction with the WorkFlow Controller and the production system.
o WorkFlow controller responsible for the orchestration and monitoring of assembly schedule execution by the available resources.
• The following MASTERLY technologies final prototypes have been tested inside the TEKNIKER pre-pilot testbed in terms of the aeronautic pilot case of the project:
o Smart crane for autonomous transportation.
o Vision-based objects' geometry estimation to precisely detect the location of the part inside the testbed’ layout.
o Digital twin at cell and process level.
o AR operator support application based on AR glasses enabling human operators interaction with the WorkFlow Controller.
o WorkFlow controller responsible for the orchestration and monitoring of assembly schedule execution by the available resources.
Through these integration activities, valuable feedback has been collected towards the fine-tuning of MASTERLY modules and the delivery of MASTERLY final prototypes at the industrial demonstrators during the 3rd period of the project.
The concept of MASTERLY is built around five building blocks, focused on collaborative robots, adaptable & modular grippers, AI-driven modules for advanced control, programming and interaction tools, and integration platform for seamless communication consisting of several modules. During the second period of the project, the consortium has finalized the list of MASTERLY modules as follows:
• Flexible robotic arm (Leader: COMAU)
• Autonomous mobile robot platform (Leader: COMAU)
• Modular gripper for flexible materials (Leader: IIT)
• Dexterous gripper for rigid parts (Leader: TF-CC)
• Intelligent stationary fixture (Leader: TEKNIKER)
• Smart crane for autonomous transportation (Leader: TEKNIKER)
• Force-based control and handling (Leader: TEKNIKER)
• Vision-based objects' geometry estimation (Leader: UNIKIEV)
• Digital twin at cell and process level (Leader: RWTH)
• Digital twin framework for mobile manipulators (Leader: LMS)
• Dynamic task and actions planning (Leader: LMS)
• AR application for operator support and robot control (Leader: LMS)
• Localization, motion planning and collision avoidance (Leader: RWTH)
• AI Vision and CAD based robot programming (Leader: LMS)
• Human tracking and body collision avoidance (Leader: LMS)
• Smart interfaces for human-production interaction (Leader: LMS)
• WorkFlow Controller (Leader: CASP)
The final integration and validation of all these technologies in the industrial demonstrators during the final period of the project will result in flexible and reconfigurable robotized solutions able to advance the research and manufacturing beyond the state of the art.
• Flexible robotic arm (Leader: COMAU)
• Autonomous mobile robot platform (Leader: COMAU)
• Modular gripper for flexible materials (Leader: IIT)
• Dexterous gripper for rigid parts (Leader: TF-CC)
• Intelligent stationary fixture (Leader: TEKNIKER)
• Smart crane for autonomous transportation (Leader: TEKNIKER)
• Force-based control and handling (Leader: TEKNIKER)
• Vision-based objects' geometry estimation (Leader: UNIKIEV)
• Digital twin at cell and process level (Leader: RWTH)
• Digital twin framework for mobile manipulators (Leader: LMS)
• Dynamic task and actions planning (Leader: LMS)
• AR application for operator support and robot control (Leader: LMS)
• Localization, motion planning and collision avoidance (Leader: RWTH)
• AI Vision and CAD based robot programming (Leader: LMS)
• Human tracking and body collision avoidance (Leader: LMS)
• Smart interfaces for human-production interaction (Leader: LMS)
• WorkFlow Controller (Leader: CASP)
The final integration and validation of all these technologies in the industrial demonstrators during the final period of the project will result in flexible and reconfigurable robotized solutions able to advance the research and manufacturing beyond the state of the art.