Types of activities developed by the institution

• Robot programming (software development)
• Research and development projects
• Training

Project 1

Period: 01/01/2018 - 31/12/2023 This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 741930)This project aim is to establish the foundations of versatile cloth manipulation by robots. The theoretical ground will be to link machine learning and computational topology methods, so as to come up with a theory of cloth deformation under manipulation leading to a general framework for robots to learn to manipulate garments from human demonstrations. Such framework will encompass: non-expert teaching of a task, robot perception and skill learning, task-oriented cloth representation, probabilistic planning, robot task execution in varying initial conditions, failure diagnosis and informed requests for human help.

Project 2

Period: 01/01/2021 - 31/12/2024 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016906 In CANOPIES, our goal is to develop a novel collaborative human-robot paradigm addressing the challenges of Human Robot Interaction and Human-Robot Collaboration in the unstructured highly dynamic outdoor environment of permanent crop farming (Agri-Food Area). Our approach will be demonstrated through an integrated system composed by farming robots and logistics robots with a real-world validation of two economically relevant agronomic operations within a table-grape vineyard: harvesting and pruning. CANOPIES represents the first attempt to introduce a collaborative paradigm in the field of precision agriculture for permanent crops where farmworkers can efficiently work together with teams of robots to perform agronomic interventions, like harvesting or pruning in table-grape vineyards.

Project 3

Period: 01/01/2021 - 30/09/2024 Social robots and other AI systems are increasingly becoming present in public spaces. In this SecuRoPS project, we will develop a user-centred security framework and investigate the challenges pertaining to the cybersecurity of autonomous social robots. The framework consists of a well-defined process, threat models, design principles, and guidelines, to manage the safety and security of social robots and AI systems. This will enhance safety, security, and privacy of citizens. The framework correspondingly offers reusable models or components that can be applied by robot developers, robot owners and other stakeholders to develop secure robots and to monitor and respond to security incidents.

Project 4

Period: 01/03/2021 - 31/12/2024 Project PCI2020-120718-2 funded by MCIN/ AEI /10.13039/501100011033 and cofunded by the "European Union NextGenerationEU/PRTR" COHERENT will develop a novel framework to combine explanations originated at the different robotic levels into a single explanation. This combination is not unique and may depend on several factors including the step into the action sequence, or the temporal importance of each information source. Robotic tasks are interesting because they entail performing a sequence of actions, and thus the system must be able to deliver these explanations also during the execution of the task, either because the user requested or actively because an unforeseen situation occurs. COHERENT will propose effective evaluation metrics oriented to the special case of explanations in HRI systems.

Project 5

Period: 01/01/2022 - 29/12/2023 Project confunded by European Union Todays logistics operations in city centres lead to very negative effects: increase in traffic congestion; safety problems for pedestrians, bikers and deliverers; air and noise pollution. To tackle these challenges, the LogiSmile partners will demonstrate in pilot cities a fully autonomous delivery system consisting of an autonomous hub vehicle that works in cooperation with smaller autonomous delivery devices. To control the robots and remotely coordinate the fleet operations, a back-end control centre will be piloted too. The robots and remote back-end control centre will be tested in different urban environments. This autonomous delivery system will reduce delivery costs, parking problems, emissions and congestion.

Project 6

Period: 01/09/2021 - 31/08/2024 Project PID2020-117509GB-I00 funded by MCIN/ AEI /10.13039/501100011033 In this project, we propose to formalize the concepts of agility and gracefulness in a quantitative way and to develop a trajectory optimizer capable of producing agile and graceful motions compatible with all the kinematic and dynamic constraints of the robot; that is to say, avoiding collisions and respecting joint bounds and limitations in the forces that the actuators can exert. Given an initial feasible trajectory, the optimizer has to improve it according to the selected cost function while still satisfying the aforementioned constraints. In particular, the proposed optimizer should be able to tackle tasks with (1) serial robots, (2) parallel robots and, in general, closed kinematic chains of any topology, and (3) fixed or mobile robots of any type manipulating a known load, all of them in environments with or without gravity.

Project 7

Period: 01/09/2021 - 31/08/2024 Project PID2020-115905RB-C21 funded by MCIN/ AEI /10.13039/501100011033 L-BEST considers research in supervision and fault-tolerant control of Smart Infrastructures by means of two related methodologies: advanced learning and optimization. The use of advanced learning from data is supported by the fact that SIs include sensors and smart-grid technology providing a continuous flow of operational data. First-principles models alone may not capture the complex behaviours of these SIs, so that a combination with learning from operational data is proposed. Optimization-based control is concerned with computing strategies which improve specific performance indicators, such as those related to efficiency and safety. Advanced optimization and learning are proposed for this type of problems in large-scale and complex SIs.

Project 8

Period: 01/09/2021 - 31/08/2024 Project PLEC2021-007817 funded by MCIN/ AEI /10.13039/501100011033 and by the "European Union NextGenerationEU/PRTR" The objective of the project is to help elderly or disabled people to maintain a healthy mental and physical life using intelligent robotics systems. This includes keeping and improving social relationships, have healthy meals and execute daily routines of physical and mental exercises. To achieve this, we propose an intelligent robotic system capable of helping people to communicate, monitor the person and motivate them mentally and physically. A human remote operator can help in case of unhandled events or risk situations in real time.

Project 9

Period: 01/12/2021 - 30/11/2024 Project PLEC2021-007859 funded by MCIN/ AEI /10.13039/501100011033 and by the "European Union NextGenerationEU/PRTR" In this project we aim to develop new enabling technologies in three core aspects: personalization, continual dialogue understanding and explainability: Personalization because robots must make decisions that adapt to the user and the caregiver needs and preferences; Continual dialoge understanding because the most natural interactions are conversations where the robot can extract useful information about the user both by asking questions or maintaining small talk dialogues; Explainability because users need to build trust by understanding why the robot takes particular decisions and what data the robot is gathering, providing mechanisms for privacy control.