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2022 - A Cognitive Architecture for Robot-Assisted Surgical Procedures [Articolo su rivista]
Zini, Elena; Minelli, Marco; Sabattini, Lorenzo; Ferraguti, Federica

2022 - Improving the Feasibility of DS-based Collision Avoidance Using Non-Linear Model Predictive Control [Relazione in Atti di Convegno]
Farsoni, S.; Sozzi, A.; Minelli, M.; Secchi, C.; Bonfe, M.

In this paper we present a novel strategy for reactive collision-free feasible motion planning for robotic manipulators operating inside an environment populated by moving obstacles. The proposed strategy embeds the Dynamical System (DS) based obstacle avoidance algorithm into a constrained non-linear optimization problem following the Model Predictive Control (MPC) approach. The solution of the problem allows the robot to avoid undesired collision with moving obstacles ensuring at the same time that its motion is feasible and does not overcome the designed constraints on velocity and acceleration. Simulations demonstrate that the introduction of the MPC prediction horizon helps the optimization solver in finding the solution leading to obstacle avoidance in situations where a non predictive implementation of the DS-based method would fail. Finally, the proposed strategy has been validated in an experimental work-cell using a Franka-Emika Panda robot.

2021 - A First Evaluation of a Multi-Modal Learning System to Control Surgical Assistant Robots via Action Segmentation [Articolo su rivista]
De Rossi, Giacomo; Minelli, Marco; Roin, Serena; Falezza, Fabio; Sozzi, Alessio; Ferraguti, Federica; Setti, Francesco; Bonfè, Marcello; Secchi, Cristian; Muradore, Riccardo

2021 - A two-layer trilateral teleoperation architecture for mentoring in surgical training [Relazione in Atti di Convegno]
Minelli, M.; Loschi, F.; Ferraguti, F.; Secchi, C.

In this paper we propose a novel trilateral dual-master-single-slave teleoperation control architecture that can be used for the training of novice surgeons in surgical procedures. Starting from the concept of energy tank, we propose a flexible and stable trilateral interconnection over a delayed communication channel between the masters and the slave. Exploiting the flexibility provided by the controller, we design a training strategy for novice surgeons. The proposed architecture is experimentally validated.

2021 - Dynamic-based RCM Torque Controller for Robotic-Assisted Minimally Invasive Surgery [Relazione in Atti di Convegno]
Minelli, M.; Secchi, C.

In this paper we propose a novel flexible and optimization-free controller for standard torque-controlled manipulator for Robotic-Assisted Minimally Invasive Surgery. A novel method has been developed to model the constraint introduced by the laparoscopic tool, i.e. the remote center of motion, exploiting closed chain manipulators theory, and the final controller was synthesized considering the effects the constraint produces at a dynamic level. A set of simulations has been performed in a trajectory tracking task to validate the performances of the proposed controller. Performances have been also tested in a real experimental scenario with a KUKA LWR 4+ with 7 degrees of freedom endowed with a laparoscopic-like tool. Results show the effectiveness of the proposed controller and its capability of modifying the trajectory in order to preserve the RCM constraint.

2021 - Feasibility of a telementoring approach as a practical training for transurethral enucleation of the benign prostatic hyperplasia using bipolar energy: a pilot study [Articolo su rivista]
Amato, M.; Eissa, A.; Puliatti, S.; Secchi, C.; Ferraguti, F.; Minelli, M.; Meneghini, A.; Landi, I.; Guarino, G.; Sighinolfi, M. C.; Rocco, B.; Bianchi, G.; Micali, S.

Introduction: Telementoring is one of the applications of telemedicine capable of bringing highly experienced surgeons to areas lacking expertise. In the current study, we aimed to assess a novel telementoring application during the learning curve of transurethral enucleation of the prostate using bipolar energy (TUEB). Material and methods: A telementoring system was developed by our engineering department. This application was used to mentor ten prospective cases of TUEB performed by an expert endourologist (novice to the TUEB). A questionnaire was filled by the operating surgeon and the mentor to provide subjective evaluation of the telementoring system. Finally, the outcomes of these patients were compared to a control group consisting of ten consecutive patients performed by the mentor. Results: Ten consecutive TUEB were performed using this telementoring application. Delayed and interrupted connection were experienced in two and one patients, respectively; however, their effect was minor, and they did not compromise the safety of the procedure. None of the patients required conversion to conventional transurethral resection of the prostate. Only one patient in our series experienced grade IIIb complication. Conclusion: The telementoring application for TUEB is promising. It is a simple and low-cost tool that could be a feasible option to ensure patients’ safety during the initial phase of the learning curve without time and locations constraints for both the mentor and the trainee; However, it should be mentioned that telementoring cannot yet replace the traditional surgical training with the mentor and trainee being in the operative room. Further studies are required to confirm the current results

2020 - Augmented Reality and Robotic-Assistance for Percutaneous Nephrolithotomy [Articolo su rivista]
Ferraguti, Federica; Minelli, Marco; Farsoni, Saverio; Bazzani, Stefano; Bonfe, Marcello; Vandanjon, Alexandre; Puliatti, Stefano; Bianchi, Giampaolo; Secchi, Cristian

2020 - Integrating model predictive control and dynamic waypoints generation for motion planning in surgical scenario [Relazione in Atti di Convegno]
Minelli, M.; Sozzi, A.; De Rossi, G.; Ferraguti, F.; Setti, F.; Muradore, R.; Bonfe, M.; Secchi, C.

In this paper we present a novel strategy for motion planning of autonomous robotic arms in Robotic Minimally Invasive Surgery (R-MIS). We consider a scenario where several laparoscopic tools must move and coordinate in a shared environment. The motion planner is based on a Model Predictive Controller (MPC) that predicts the future behavior of the robots and allows to move them avoiding collisions between the tools and satisfying the velocity limitations. In order to avoid the local minima that could affect the MPC, we propose a strategy for driving it through a sequence of waypoints. The proposed control strategy is validated on a realistic surgical scenario.

2020 - Self-optimization of resilient topologies for fallible multi-robots [Articolo su rivista]
Minelli, Marco; Panerati, Jacopo; Kaufmann, Marcel; Ghedini, Cinara; Beltrame, Giovanni; Sabattini, Lorenzo

2020 - Technical and Functional Validation of a Teleoperated Multirobots Platform for Minimally Invasive Surgery [Articolo su rivista]
Leporini, Alice; Oleari, Elettra; Landolfo, Carmela; Sanna, Alberto; Larcher, Alessandro; Gandaglia, Giorgio; Fossati, Nicola; Muttin, Fabio; Capitanio, Umberto; Montorsi, Francesco; Salonia, Andrea; Minelli, Marco; Ferraguti, Federica; Secchi, Cristian; Farsoni, Saverio; Sozzi, Alessio; Bonfe, Marcello; Sayols, Narcis; Hernansanz, Albert; Casals, Alicia; Hertle, Sabine; Cuzzolin, Fabio; Dennison, Andrew; Melzer, Andreas; Kronreif, Gernot; Siracusano, Salvatore; Falezza, Fabio; Setti, Francesco; Muradore, Riccardo

2019 - An energy-shared two-layer approach for multi-master-multi-slave bilateral teleoperation systems [Relazione in Atti di Convegno]
Minelli, M.; Ferraguti, F.; Piccinelli, N.; Muradore, R.; Secchi, C.

In this paper, a two-layer architecture for the bilateral teleoperation of multi-arms systems with communication delay is presented. We extend the single-master-single-slave two layer approach proposed in [1] by connecting multiple robots to a single energy tank. This allows to minimize the conservativeness due to passivity preservation and to increment the level of transparency that can be achieved. The proposed approach is implemented on a realistic surgical scenario developed within the EU-funded SARAS project.

2019 - Cognitive Robotic Architecture for Semi-Autonomous Execution of Manipulation Tasks in a Surgical Environment [Relazione in Atti di Convegno]
De Rossi, Giacomo; Minelli, Marco; Sozzi, Alessio; Piccinelli, Nicola; Ferraguti, Federica; Setti, Francesco; Bonfe, Marcello; Secchi, Cristian; Muradore, Riccardo

2019 - Robust area coverage with connectivity maintenance [Relazione in Atti di Convegno]
Siligardi, L.; Panerati, J.; Kaufmann, M.; Minelli, M.; Ghedini, C.; Beltrame, G.; Sabattini, L.

Robot swarms herald the ability to solve complex tasks using a large collection of simple devices. However, engineering a robotic swarm is far from trivial, with a major hurdle being the definition of the control laws leading to the desired globally coordinated behavior. Communication is a key element for coordination and it is considered one of the current most important challenges for swarm robotics. In this paper, we study the problem of maintaining robust swarm connectivity while performing a coverage task based on the Voronoi tessellation of an area of interest. We implement our methodology in a team of eight Khepera IV robots. With the assumptions that robots have a limited sensing and communication range - and cannot rely on centralized processing - we propose a tri-objective control law that outperforms other simpler strategies (e.g. a potential-based coverage) in terms of network connectivity, robustness to failure, and area coverage.

2019 - Robust connectivity maintenance for fallible robots [Articolo su rivista]
Panerati, Jacopo; Minelli, Marco; Ghedini, Cinara; Meyer, Lucas; Kaufmann, Marcel; Sabattini, Lorenzo; Beltrame, Giovanni

Multi-robot systems are promising tools for many hazardous real-world problems. In particular, the practical application of swarm robotics was identified as one of the grand challenges of the next decade. As swarms enter the real world, they have to deal with the inevitable problems of hardware, software, and communication failure, especially for long-term deployments. Communication is a key element for effective collaboration, and the ability of robots to communicate is expressed by the swarm’s connectivity. In this paper, we analyze a set of techniques to assess, control, and enforce connectivity in the context of fallible robots. Past research has addressed the issue of connectivity but, for the most part, without making system reliability a constitutional part of the model. We introduce a controller for connectivity maintenance in the presence of faults and discuss the optimization of its parameters and performance. We validate our approach in simulation and via physical robot experiments.

2019 - Stop, Think, and Roll: Online Gain Optimization for Resilient Multi-robot Topologies [Relazione in Atti di Convegno]
Minelli, Marco; Kaufmann, Marcel; Panerati, Jacopo; Ghedini, Cinara; Beltrame, Giovanni; Sabattini, Lorenzo

Stop, Think, and Roll: Online Gain Optimization for Resilient Multi-robot Topologies