SOFTMANBOT is an industrial-end-user driven project that will provide an innovative and holistic robotic system for the handling of flexible and deformable materials within labour-intensive production processes. The robotic system will be composed by three main pillars including a generic robotic perception system (perception of the product and the human operator), a multi-sensor control and planning platform (advanced control algorithms for shape and contact servoing, AI based task generalization) and smart dexterous grippers (smart mechanical design which will embody grasping/manipulation skills and integrate sensors – mainly tactile – for identifying precisely the contact state between the product and the gripper) able to handle soft components with high-levels of robustness and flexibility. The automation solution is aimed to work in close collaboration with human operators in order to help them in the execution of contact-based challenging tasks so that the productivity and job quality will be boosted which will highly contribute to bring back production to Europe. Special attention will be paid to the integration of novel robotic concepts based on aspects of safety, ergonomics, adaptability, acceptance and user experience. In order to facilitate the assessment of the performance, transferability, scalability and large scale deployment of these solutions, the demonstrations will be conducted under real industrially relevant environments in four pilot demonstrators involving four key manufacturing sectors – toy, textile, footwear and tyre –. The project is not just aiming at quantitative improvements brought by cutting-edge technologies in a specific sector, but to use technology innovation to support a change of paradigm where handling of soft materials with the involvement of robots become a feasible and widespread alternative for European factories, specially SMEs.
We have a joint laboratory with Honda Research Institute Japan (HRI-JP) whose main aim is to develop advanced control, perception, and planning algorithms for human-robot collaboration scenarios.
The joint lab keywords, which characterise the research we develop, are ergonomy, cobots, and human-robot collaboration.
Besides iCub, the conceived algorithms for human-robot collaboration will be tested on the ED-2R and Asimo humanoid robots.
Danieli Automation’s joint lab focuses on the development of flexible robotic systems and automated solutions in the field of steel processing.
Our aim is to increase safety for workers in hazardous industrial environments by using advanced control, perception and planning algorithms.
The Camozzi Group is a market leader in the production of components for the pneumatics automation with applications in the life science, health and the textile industry.
As a research line, we are applying our expertise in the modeling, control, and planning of nonlinear systems to the pneumatic field.
The goal of the project is to devise future wearable technologies and humanoid robots to maximise work ergonomy and technological acceptability of future industry and healthcare environments.
INAIL is the Italian National Institute for Insurance against Accidents at Work, it is a public authority that manages compulsory insurance against accidents at work and occupational diseases.
The collaboration aims to adapt the iCub Robot’s Avatar architecture to develop a commercial, human-controlled wheeled Avatar Robot in a simulation environment. We will establish the Avatar simulation infrastructure to ensure seamless component operation. The project will integrate advanced manipulation, voice, and visual interfaces for better human-robot interaction, and implement tactile feedback and locomotion controls for precise and realistic movements.
The spin-off idea from AMI is aiming at providing an integrated platform that enables real-time human health monitoring in terms of motion tracking, articular stress monitoring, and fatigue analysis. Based on our extensive and in-depth research analysis, we developed groundbreaking technology.
iFeel will be the next step for life-logging human health monitoring for industrial, rehabilitation, sports and gaming applications.
Completed projects
Marie Sklodowska-Curie Innovative Training Networks under Grant Agreement No. 642667
Role: supervision of a PhD student funded by the project
Research and Innovation Programme under Grant Agreement No. 731540
Role: coordination - Francesco Nori - and PI - Daniele Pucci.
FP7