Advanced Robotics research concentrates on an innovative, multidisciplinary approach to humanoid design and control, and the development of novel robotic components and technologies. This encompasses activities from both the hard (mechanical/ electrical design and fabrication, sensor systems, actuation development etc.) and soft (control, computer software, human factors etc) systems areas of robotics.
The Biomedical Robotics Laboratory focuses on research and development of human-centered robotic technologies. We are a highly multidisciplinary group working towards the creation of novel technologies that can directly impact the health and well-being of people.
The overall research theme involves the creation of robotic systems to augment human capabilities through enhanced interfaces. This includes research in areas such as robot-assisted surgery, micromanipulation, human-robot interfaces, assistive systems for the disabled, medical imaging and computer vision, teleoperation, cognitive controllers, and automation. Typical goals are to improve the consistency, efficiency, usability and safety of difficult and/or delicate operations traditionally performed manually.
The Biomedical Robotics Laboratory is part of the Advanced Robotics Department and counts with a larger range of state-of-the-art equipment that support our research and stimulate the curiosity of our researchers. These include surgical laser systems, microscopes, motorized micromanipulators, haptic devices, EEG systems, robotic arms, endoscopes, and many other scientific instruments. We also have a dedicated room for Class-IV laser experiments, where novel laser microsurgery prototypes are developed and safely tested.
We deeply believe in collaborations to speed-up the progress of human-centered technologies and achieve meaningful results. Therefore, we are always open to new and challenging opportunities to collaborate with other groups and institutions. The multidisciplinarity of our research is a result of this vision. We currently have collaborations in the medical robotics area with the San Martino Hospital (ENT Department, UNIGE), NearLab (Politecnico di Milano), AIMS Academy (Niguarda Hospital), ALTAIR Laboratory (University of Verona), and El.En S.r.l. (Firenze). In addition, we are developing novel assistive systems for ALS patients with the Fondazione Roma.
Lead Researcher: Leonardo De Mattos
Our group works on the development of wearable assistive exoskeletons. The objective of these devices is to assist people during physical activities. Target users span from industrial workers, aiming to reduce musculoskeletal loads and the associated risk of injuries, to people with movement impairments due to conditions such as stroke or spinal injury, aiming to enable to to carry out activities of daily living.
From a research perspective, our group focuses on advances that will enable exoskeletons to succeed in real-life applications. This includes high-performance actuation systems, with the target of keeping weight and power consumption to a minimum while producing substantial physical assistance and promoting comfort. Our research comprises also assistive strategies based on the combination of relevant measurements from the environment with biosignals from the user. Our group strives to maximise the deployability of the developed devices in real-life scenarios. To this end, our approach considers the invasiveness and costs associated to the physical interfaces. Additionally, we seek to inform the development of our devices by frequently evaluating them in user studies.
Our team has developed a wearable robotic back support device, within the context of the Robo-Mate EU Project. This system is aimed to the assistance of the operators in industry during manual handling tasks and in awkward positions. Its goal is to offload the user’s low back, thereby reducing the associated pain and risk of injury.
We are currently developing a soft biomimetic exoskeleton to assist people with mobility impairments, within the context of the XoSoft EU Project.
This project will deliver a modular exoskeleton for the lower limb made of soft materials as an assistive device for persons with low to moderate mobility restrictions. The development of exoskeletons using soft materials is an innovative field with many relevant potential applications. Approaches allowing more compact, low weight and comfortable solutions are strongly needed. A small number of important developments in this respect have been made, which will enable the development of soft exoskeletons.
We are currently collaborating with a broad number of research institutions and companies with common interests in the area of wearable assistive robots.
We have a narrow collaboration with:
- research groups at ZHAW (Zürcher Hochschule für Angewandte Wissenschaften) - Departments of mechatronics and physiotheraphy
- UL (University of Limerick) - Department of human factors and ergonomics
- CSIC (Consejo Superior de Investigaciones Científicas) - Center of automotion and robotics
- Fraunhofer - Institute for industrial engineering
- Saxion university of applied science
- RRD (Roessingh Research and Development)
Industrial collaborations are also a core part of our activities. We are currently licensing the Robo-Mate technology to German Bionic Systems, while our narrow collaboration with CRF (Centro Ricerche Fiat) helps to keep our developments in industrial exoskeletons close to the real applications. Our recent collaboration with INAIL (Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro) will represent a big leap in the state-of-the-art of industrial exoskeletons.
Lead Researcher: Jesus Ortiz
Advanced Industrial Automation Lab
In the last few years, various manufacturing industries wishing to explore robotic manipulation, automatic inspection etc …have shown a growing interest in our lab. In the last few years, various manufacturing industries wishing to explore robotic manipulation, automatic inspection etc …have shown a growing interest in our lab. This has been possible thanks to the introduction of robots as something more than “simple” research prototypes. The Advanced Industrial Automation Lab (AIAL) has been set up exactly for this purpose. AIAL relies on a team of experts having the necessary skills and know how to liaise with manufacturing industries in the diverse facets they operate: from quality control to process automation. Our focus is both on innovation and research, the areas where technical consultancy is not frequent due to lack of skills, lack of resources or resistance to the introduction of new technologies in consolidated industrial environments. AIAL is devoted to technology transfer with the aim of projecting the results obtained in robotics on to the industry thanks to collaborations with other European researchers and experts. The interdisciplinarity is our key brick, both in skills and mission. Our job spans from dynamics to control and from the innovation to research.
AIAL’S activities are divided into 2 main areas: AIAL’S activities are divided into 2 main areas:
The innovation area aims to apply new technologies directly to the industrial world. This activity requires a high level of fine-tuning between companies’ needs and the research output produced by IIT. Companies frequently need to develop a medium-term vision about their technological renewal, which would entail a significant review of their production processes. AIAL comes right into this and does its best to support them in their innovation goals. The most important projects the lab has been involved in include the following companies: GE AVIO AEREO, Tetra Pak, Fameccanica Group, ANSALDO ENERGIA, etc.
The research area focuses on the development of new technologies likely to be applied to the industry in the near future. Here companies with a long-term vision of their manufacturing activities are the main actors involved. Current projects include light and fast robotics arms to increase safety at work, high-speed manipulators, sensors to detect forms of peripheral neuropathy to the lower and upper limbs and cardboard boxes production. Most projects have been financed through internal IIT funds and EU grants (Autorecon, EuroC and WearHap). One primary aspect connected to this activity is the development of numerical models capable of making the design of future mechanisms more accurate and faster. In this respect, a collaboration with MSC.Software is currently active.
LaboratoriesThe Advanced Industrial Automation Lab has several platforms (ABB anthropomorphic robot, manipulators, grippers, medical devices, inspection robots, test rigs, etc.) to investigates the performances and validate the virtual models of robots. Moreover in the ADVR there are the state-of-the-art facilities to develop, build and test legged robots (Co-Man, HyQ, HyQ2Max, Walk-Man and Centaurus) with compliant electrical and hydraulic actuation.
The AIAL collaborates mainly with industries (GE AVIO AEREO, Tetra Pak, Fameccanica Group, ANSALDO ENERGIA, etc.), but also with universities and other research centres thanks to the European Projects (Autorecon, EuroC, WearHap) and/or the collaboration within research projects (Politecnico di Torino, King’s College of London, Spedali Civili di Brescia, Università Politecnica delle Marche, etc.).
Lead Researcher: Ferdinando Cannella
The Active Perception and Robot Interactive Learning (APRIL) laboratory focuses on the co-evolution of artificial intelligence and robotic technologies to drive breakthrough research to enable robots to perform complex tasks in real world such as manufacturing, logistics, healthcare, agri-food, and more. Robots should be able to learn new skills by interacting with humans and perceiving the environments using modern robot vision and learning techniques.
The overall research theme involves the creation of various robot perception and manipulation systems to augment robot capabilities of working in complex and dynamical environments. This includes research in areas such as robot active perception, robot learning and manipulation, robot deep reinforcement learning, robot sim2real learning, as well as development of novel robot mobile manipulation systems including smart end-effectors, sensing modules.
The APRIL Laboratory is part of the Advanced Robotics Department and counts with a range of state-of-the-art equipment that support our research and stimulate the curiosity of our researchers. The equipment includes customized robot mobile manipulators, Franka Emika robot arm, Kinova GEN3 robot arm, Schunk robot arm, robot grippers, dexterous robot hands, F/T sensors, RGB and depth cameras, server with high-performance GPU farms, etc. The researchers come from multi-disciplinary backgrounds, including computer science, robotics, mechatronics, electronics.
- Learning control for robot dexterous manipulation tasks
- Sim2Real deep reinforcement learning for robot manipulation
- Objects detection, segmentation and tracking for manipulation
- Action-perception coupled whole-body control for mobile manipulator
- One-shot/Few-shot learning for robot grasping and picking
AutoMAP: AutoMAP (EU FP7 EUROC AutoMAP) addresses applications of robotic mobile manipulation in unstructured environments as found at CERN. This project is based on use case operations to be carried out on CERN’s flagship accelerator, the Large Hadron Collider. The main objective is to carry out the maintenance work using a remotely controlled robot mobile manipulator to reduce maintenance personnel exposure to hazards in the LHC tunnels – such as ionising radiation and oxygen deficiency hazards. A second goal is to allow the robot being able to autonomously carry out the same tasks in the assembly facility as in the tunnel on collimators during their initial build and quality assurance through the robot learning technologies.
Learn-Real: LEARN-REAL (EU H2020 Chist-Era Learn-Real) proposes to learn manipulation skills through simulation for object, environment and robot, with an innovative toolset comprising: i) a simulator with realistic rendering of variations allowing the creation of datasets and the evaluation of algorithms in new situations; ii) a virtual-reality interface to interact with the robots within their virtual environments, to teach robots object manipulation skills in multiple configurations of the environment; and iii) a web-based infrastructure for principled, reproducible and transparent benchmarking of learning algorithms for object recognition and manipulation by robots. Strong AI oriented technologies (Deep Reinforcement Learning, Deep Learning, Sim2Real transfer learning) are our main concerns in this project.
VINUM: VINUM, namely Grape Vine Recognition, Manipulation and Winter Pruning Automation (VINUM), is an Agri-Food project funded by the IIT-Unicatt Joint Lab. The objective is to apply the state-of-the-art mobile manipulation platforms and systems, a wheeled mobile platform with a commercial full torque sensing arm and multiple sensors, and an under-develop quadruped robot mobile platform with a customized robotic arm and multiple sensors (Cooperated with DLS research line led by Dr. Claudio Semini, for various maintenance and automation work in the vineyard, e.g., pruning, inspecting to tackle the shortage of skilled workers. Together with Learn-Real project, VINUM is targeting at providing very robust solutions for outdoor application to deal with all kinds of natural objects.
We welcome all kinds of collaborations to speed-up the progress of intelligent robotic technologies and to achieve meaningful results. Therefore, we are always open to new and challenging opportunities to collaborate with other groups and institutions. We are also open to interested students and scholars who want to spend some short time for visiting or longer time for PhD or Post-doc in the group. In the past years, we have collaborated in the robotics area with: German Aerospace Center (Germany), European Nuclear Research (Switzerland), Prisma Lab @ Università degli Studi di Napoli Federico II (Italy), Robot Learning & Interaction Group @ Idiap research institute (Switzerland), Department of Sustainable Crop Production @ Università Cattolica del Sacro Cuore (Italy), Robotics Institute @ Shenzhen Academy of Aerospace Technology (China), Department of mathmetics @ École Centrale de Lyon (France).
Lead Researcher: Fei Chen