The ROSSINI project aims to develop a disruptive, inherently safe hardware-software platform for the design and deployment of human-robot collaboration (HRC) applications in manufacturing. By combining innovative sensing, actuation and control technologies (developed by world market leaders in their field), and integrating them in an open development environment, the ROSSINI platform will deliver a set of tools which will enable the spread of HRC applications where robots and human operators will become members of the same team, increasing job quality, production flexibility and productivity.
Thanks to enhanced robot sensing capabilities, the deployment of artificial intelligence to optimise productivity and safety, and natively collaborative manipulation technologies, ROSSINI will deliver high performance HRC workcells, combining the safety of traditional cobots with the working speed and payloads of industrial robots.
The ROSSINI research lines will this be:
- SENSING: A high performance Smart and Safe Sensor System for human and robot detection & tracking, capable of quickening sensors response time by 70%
- CONTROL: A safety aware control architecture for robot dynamic reconfiguration, capable of reducing robot task execution time by 45%
- ACTUATION: An innovative, collaborative by birth robot manipulator, to be marketed through the ROSSINI platform, capable of increasing the working speed when collaborating with humans by 45%
- HUMAN FACTORS: Human factors analysis for mutual predictability of robot and human intentions, capable of increasing job quality index by 15%
- RISK ASSESSMENT: A risk assessment procedure based on new interpretation of collision values, capable of reducing (combined with other results) by 30% the time and cost of reconfiguration, and increasing the allowed robot working speed by 20%
The research lines will be combined into 3 demonstrators (white goods, electronic equipment, and food packaging).
|Total budget - Public funding:||7 978 176,00 Euro - 7 978 176,00 Euro|
|Call topic:||Effective Industrial Human-Robot Collaboration (RIA) (DT-FOF-02-2018)|
This is a set of Specific Objectives and Research & Innovation Objectives that is subject to a consultation in preparation of the Made In Europe Partnership. For more guidance about the consultation, please see www.effra.eu/made-in-europe-state-play.
AI for flexible execution plan definition
Collaborative robot solutions to assist final customer in the production line (see T8.3 - Food Products Packaging use case)
Virtual tool to design innovative robotic cells
Virtual tool to design innovative robotic cells
Job quality evaluation and optimal task allocation betweek humans and robots (WP6).
Use cases for different set-ups and needs
More flexible production and industrial processes reorganisation
Definition of guidelines and proof of concept validation for both large enterprises and SMEs (see WP9)
- ROSSINI Smart and Safe Sensing System
- Safety Aware Control Architecture
- Collaborative by Birth Robotic Arm
- Human-robot mutual understanding framework
- Integration and Validation Layer
ROSSINI will develop and demonstrate technologies enabling a significant advancement in HRC. They are:
These technologies will be then integrated into the ROSSINI Platform architecture.
Expected achievements: 15% increase in OECD Job Quality Index through work environment and safety improvement; 20% reduction in production reconfiguration time and cost; reduction of heavy works impacts and costs: increase in the overall job satisfaction and job attractiveness; increased value-chain integration and stakeholder satisfaction
HRC applications pose several challenges to the manufacturing industry which sees an increased need for automation and scalability, notably in SMEs. Moreover, at the moment, HRC applications imply also huge investments in terms of effort, time and intellectual capital to integrate robots and sensors into the manufacturing workflow which can’t be afforded by most of the European SMEs, notably if the production combines low volume with high mix. Trough ROSSINI project, implementation of real and cost effective HRC will allow to redesign workplaces combining automation and lean manufacturing concept, with a drastic reduction of conversion and reconfiguration costs.
The ROSSINI project foresees 3 use-cases related to Domestic Appliances Assembly (WHIRLPOOL), Electronic Components Production (SCHINDLER) and Food Products Packaging (IMA). The 1st use case aims at implementing real and efficient HRC which will allow to enhance human health and satisfaction in workplaces combining automation and the lean manufacturing concept thus reducing costs and avoiding dangerous operations for workers (requirement: improving safety in HRC and maintain the efficiency of the production line). The 2nd use case wants to redesign the actual production line where individually separate but related items are grouped (the kitting step), packaged (the assembly step) and supplied together as one unit (requirement: strict collaboration between human operators and robot). The 3rd use case will leverage on a mobile robotic solution and an advanced smart sensing system to improve its current robotic solution for assisting operator in machine monitoring and maintenance (requirement: improve system performance in terms of speeds, handled objects and capabilities, whilst maintain operator safety)
Not available yet
Cobots and in general HRC solutions, which can be used for multiple functions due to their flexibility in deployment, offer higher returns on investment and faster payback, compared to legacy industrial robots. Moreover, cobots’ safety features and ease of use make integration and implementation less costly than the traditional industrial robots. In high-cost countries, having skilled human workers engaged in suitable configured manufacturing, assembly, finishing and inspection operations side by side with cobots is one of the most cost- effective ways to leverage the unique value-adding capabilities of a skilled human workforce
The workcells employing the ROSSINI human-robot mutual understanding framework will increase production flexibility by 5%.
The joint action of the dynamic scheduler and of the dynamic planner can lead to a reduction of up to 45% of the overall task execution time
ROSSINI will develop a Design Level that will allow users to follow and evaluate process designs on multiple dimensions, where job quality and related metrics will be the primary outcomes together with productivity, product quality and cost
HRC solutions make it possible to integrate production machinery, warehousing systems and production facilities into single human-centred cyber-physical systems. As such, the traditional frontier between the production and logistical tasks of manufacturing can be expected to become increasingly interconnected. Lastly, an increased uptake of HRC will lead to a change in the robotics value chain itself. Suppliers, integrators and users are bound to collaborate more intensively which is already leading to new business models such as rental/leasing agreements, pay-on-production, predictive maintenance, etc.
ROSSINI will deliver high performance HRC workcells, combining the safety of traditional cobots with the working speed and payloads of industrial robots, capable of optimising task execution. This will trigger manufacturers’ investment in HRC technology, increasing European factories productivity and thus competitiveness versus low-cost manufacturers.
ROSSINI is expected to unleash new market opportunities for the consortium industrial partners, resulting in a total yearly turnover of worth 125M€ by 2027
ROSSINI will help European factories to attract skilled workforce in factories because of the attention paid to job quality and employee satisfaction
ROSSINI ambition is to develop a framework for Human-Robot Mutual Understanding in collaborative operations which will incorporate a human-centred process design level to address and account for human factors like job quality, user experience, trust, feeling of safety, and liability, in the early design stages.
The Rossini Smart and Safe Sensing System (RS4) will combine information from several different customised sensing technologies (Vision, Laser Scanning, Radar, Mat, etc.) in order track not only the position but also the speed of each operator and object in the scene, thus ensuring operators’ safety. Moreover, the use of cobots will reduce the amount of working hours spent in physical working thus shifting the workforce away from more physically laborious tasks, towards those of assembly, programming etc. In this way, jobs could become more interesting given their need for higher levels of creativity, problem solving and decision making, definitively resulting in an improved job satisfaction.
The RS4 will allow to improve safety also for standard robots
The ROSSINI project will develop an integrated set of components for robotic
workcells, capable of increasing job quality and reducing reconfiguration time.
ROSSINI will provide several advances beyond the state of the art, developing a Safety Aware Control Architecture for robot cognitive perception and optimal task planning and execution. In order to enable actual perception, ROSSINI will deploy a data processing technique based on artificial intelligence, taking advantage of GPU computing and advanced machine learning algorithms for real-time image recognition, to obtain a semantic scene map that adapts to dynamic working conditions. ROSSINI will adopt AI algorithms also for motion prediction of humans and moving entities, and will embed their stochastic information in the dynamic semantic scene map. This will allow the robot to further refine its planning in order to maximize performance while preserving safety. Moreover, the deployment of artificial intelligence techniques for data processing will not be just aimed to enable robot perception, but will also make robot cognition possible. ROSSINI Safety Aware Control Architecture will make it possible for robots to optimally schedule the tasks reacting to a changing environment. Each action to be executed will be sent to a dynamic planner that will dynamically optimize its execution in terms of trajectory to follow and/or interactive behaviour to reproduce while considering the variable safety conditions in the working area. In this way, ROSSINI will reach the goal to optimise the trade-off between human operator safety and manufacturing productivity and will introduce a novel perception and control architecture blending safety and performance oriented planning/control.
The contribution of the ROSSINI project could be very effective to provide useful insights to the regulatory scenario, as the project will aim to design and develop innovative robotic solutions characterized by built-in safety features, and a safety aware control architecture.
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- | DATALOGIC SRL (DATALOGIC) (Coördinator)
- | CORE INNOVATION AND TECHNOLOGY OE
- | CRIT Research Srl
- | DATALOGIC IP TECH SRL (DLIPTECH)
- | FRAUNHOFER GESELLSCHAFT
- | I.M.A. INDUSTRIA MACCHINE AUTOMATICHE SPA (IMA)
- | INDESIT COMPANY S.P.A.
- | INDUSTRIELE MECHANISATIE OF AUTOMATISATIE NV (MACHINEBOUW)
- | IRIS
- | PILZ GMBH & CO. KG (PILZ)
- | SCHINDLER SUPPLY CHAIN EUROPE AG (SCHINDLER)
- | TNO - Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek
- | University of Modena and Reggio Emilia
- | University of applied sciences and arts of southern switzerland (SUPSI)